From c94c37156ec134e68184b1e4821f6a87032a9172 Mon Sep 17 00:00:00 2001 From: kgryte Date: Tue, 12 Mar 2019 16:52:35 -0700 Subject: [PATCH 001/142] Use non-deprecated mode --- lib/node_modules/@stdlib/repl/server/lib/defaults.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/repl/server/lib/defaults.js b/lib/node_modules/@stdlib/repl/server/lib/defaults.js index 327cace54ec5..b8c854f3050c 100644 --- a/lib/node_modules/@stdlib/repl/server/lib/defaults.js +++ b/lib/node_modules/@stdlib/repl/server/lib/defaults.js @@ -42,7 +42,7 @@ function options() { 'output': process.stdout, 'useGlobal': false, 'ignoreUndefined': true, - 'replMode': repl.REPL_MODE_MAGIC + 'replMode': repl.REPL_MODE_SLOPPY }; return opts; } From 5ea499ab6f24ff671cc67b1dcf466a1e8ae5e906 Mon Sep 17 00:00:00 2001 From: kgryte Date: Tue, 12 Mar 2019 16:53:07 -0700 Subject: [PATCH 002/142] Update wording --- lib/node_modules/@stdlib/iter/dedupe-by/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/iter/dedupe-by/README.md b/lib/node_modules/@stdlib/iter/dedupe-by/README.md index 3637c3bfdd3d..eacc9a0e7883 100644 --- a/lib/node_modules/@stdlib/iter/dedupe-by/README.md +++ b/lib/node_modules/@stdlib/iter/dedupe-by/README.md @@ -76,7 +76,7 @@ The returned [iterator][mdn-iterator-protocol] protocol-compliant object has the - **next**: function which returns an [iterator][mdn-iterator-protocol] protocol-compliant object containing the next iterated value (if one exists) assigned to a `value` property and a `done` property having a `boolean` value indicating whether the [iterator][mdn-iterator-protocol] is finished. - **return**: function which closes an [iterator][mdn-iterator-protocol] and returns a single (optional) argument in an [iterator][mdn-iterator-protocol] protocol-compliant object. -The provided function is provided five arguments: +The callback function is provided five arguments: - **curr**: current source iterated value. - **sprev**: previous source iterated value. From 806b7f7c952d698f077aaa2758343d70f02099cd Mon Sep 17 00:00:00 2001 From: rinbo Date: Tue, 12 Mar 2019 21:37:54 +0100 Subject: [PATCH 003/142] Add licence header --- .../@stdlib/math/base/special/cosc/README.md | 21 +++++++++++++++++++ 1 file changed, 21 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/README.md diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/README.md b/lib/node_modules/@stdlib/math/base/special/cosc/README.md new file mode 100644 index 000000000000..37cde05d900e --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/README.md @@ -0,0 +1,21 @@ + + +# Computes derivative of the cardinal sine function From 62640bd99370b68e6064e57f2e6aebf289255b32 Mon Sep 17 00:00:00 2001 From: rinbo Date: Tue, 12 Mar 2019 21:48:01 +0100 Subject: [PATCH 004/142] Add package.json --- .../math/base/special/cosc/package.json | 65 +++++++++++++++++++ 1 file changed, 65 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/package.json diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/package.json b/lib/node_modules/@stdlib/math/base/special/cosc/package.json new file mode 100644 index 000000000000..a135c3511da5 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/math/base/special/cosc", + "version": "0.0.0", + "description": "Compute the derivative of the normalized cardinal sine of a number.", + "license": "Apache-2.0", + "author": { + "name": "Maybe me?", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "sin", + "sinc", + "sine", + "cardinal", + "trig", + "trigonometry", + "normalized", + "cosc" + ] +} From 97d18ae158755c39a2b089bda9331ef5bb81462a Mon Sep 17 00:00:00 2001 From: rinbo Date: Wed, 13 Mar 2019 21:21:41 +0100 Subject: [PATCH 005/142] Add cosc.js --- .../math/base/special/cosc/lib/cosc.js | 91 +++++++++++++++++++ .../math/base/special/cosc/package.json | 2 +- 2 files changed, 92 insertions(+), 1 deletion(-) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js new file mode 100644 index 000000000000..75d11bc1e980 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js @@ -0,0 +1,91 @@ +/** + * @license Apache-2.0 + * + * Copyright (c) 2019 The Stdlib Authors. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +'use strict'; + +// MODULES // + +var sinpi = require('@stdlib/math/base/special/sinpi'); +var cospi = require('@stdlib/math/base/special/cospi'); +var isnan = require('@stdlib/math/base/assert/is-nan'); +var isInfinite = require('@stdlib/math/base/assert/is-infinite'); +var PI = require('@stdlib/constants/math/float64-pi'); + + +// MAIN // + +/** + * Computes the derivative of the normalized cardinal sine of a number. + * + * ## Method + * + * For \\( x \neq 0 \\), the derivative of \operatorname{sinc}(x) is calculated as + * + * ```tex + * \operatorname{cosc}(x) = \frac{\operatorname{cos}(\pi x)}{x} - \frac{\operatorname{sin}(\pi x)}{\pi x^2} + * ``` + * + * + * ## Special Cases + * + * ```tex + * \begin{align*} + * \operatorname{cosc}(0) &= 0 & \\ + * \operatorname{cosc}(\infty) &= 0 & \\ + * \operatorname{cosc}(-\infty) &= 0 & \\ + * \operatorname{cosc}(\mathrm{NaN}) &= \mathrm{NaN} + * \end{align*} + * ``` + * + * + * @param {number} x - input value + * @returns {number} derivative of normalized sinc(x) + * + * @example + * var v = cosc( 0.5 ) + * // return ~-1.273 + * + * @example + * var v = cosc( -1.2 ) + * // return ~0.544 + * + * @example + * var v = cosc( 0.0 ) + * // return 0 + * + * @example + * var v = cosc( NaN ) + * // return NaN + */ +function cosc(x) { + if (isnan(x)) { + return NaN; + } + if (isInfinite(x)) { + return 0.0; + } + if (x === 0.0) { + return 0.0; + } + return ( cospi(x) - ( sinpi(x) / ( PI * x ))) / x; +} + + +// EXPORTS // + +module.exports = cosc; diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/package.json b/lib/node_modules/@stdlib/math/base/special/cosc/package.json index a135c3511da5..8cbfe2f8b032 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/package.json +++ b/lib/node_modules/@stdlib/math/base/special/cosc/package.json @@ -4,7 +4,7 @@ "description": "Compute the derivative of the normalized cardinal sine of a number.", "license": "Apache-2.0", "author": { - "name": "Maybe me?", + "name": "The Stdlib Authors", "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" }, "contributors": [ From ec4b0d9263abd4d915f0a433a036e75b06d07f3e Mon Sep 17 00:00:00 2001 From: rinbo Date: Wed, 13 Mar 2019 21:25:24 +0100 Subject: [PATCH 006/142] Add index.js for lib dir --- .../math/base/special/cosc/lib/index.js | 49 +++++++++++++++++++ 1 file changed, 49 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/lib/index.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/lib/index.js b/lib/node_modules/@stdlib/math/base/special/cosc/lib/index.js new file mode 100644 index 000000000000..d241c35141b9 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/lib/index.js @@ -0,0 +1,49 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the derivative of the normalized cardinal sine of a number. +* +* @module @stdlib/math/base/special/cosc +* +* @example +* var cosc = require( '@stdlib/math/base/special/cosc' ); +* +* var v = cosc( 0.5 ); +* // returns ~-1.273 +* +* v = cosc( -1.2 ); +* // returns ~-0.544 +* +* v = cosc( 0.0 ); +* // returns 0.0 +* +* v = cosc( NaN ); +* // returns NaN +*/ + +// MODULES // + +var cosc = require( './cosc.js' ); + + +// EXPORTS // + +module.exports = cosc; From 725c50d17cd0b92a751630e03af3e360af3bf58e Mon Sep 17 00:00:00 2001 From: rinbo Date: Wed, 13 Mar 2019 22:19:55 +0100 Subject: [PATCH 007/142] Add Julia test fixtures --- .../cosc/test/fixtures/julia/data.json | 1 + .../test/fixtures/julia/large_negative.json | 1 + .../test/fixtures/julia/large_positive.json | 1 + .../cosc/test/fixtures/julia/runner.jl | 80 +++++++++++++++++++ .../test/fixtures/julia/tiny_negative.json | 1 + .../test/fixtures/julia/tiny_positive.json | 1 + .../math/base/special/cosc/test/tests.js | 0 7 files changed, 85 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/large_negative.json create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/large_positive.json create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json new file mode 100644 index 000000000000..d326f74a2658 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/large_negative.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/large_negative.json new file mode 100644 index 000000000000..f42ea6c60a5f --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/large_negative.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl new file mode 100644 index 000000000000..4b9d7ab2948a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl @@ -0,0 +1,80 @@ +#!/usr/bin/env julia +# +# @license Apache-2.0 +# +# Copyright (c) 2018 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import JSON + +""" + gen( x, name ) + +Generate fixture data and write to file. + +# Arguments + +* `x`: domain +* `name::AbstractString`: output filename + +# Examples + +``` julia +julia> x = range( -708, stop=709, lenght=2001 ); +julia> gen( x, \"data.json\" ); +``` +""" +function gen( x, name ) + y = cosc.( x ); + + # Store data to be written to file as a collection: + data = Dict([ + ("x", x), + ("expected", y) + ]); + + # Based on the script directory, create an output filepath: + filepath = joinpath( dir, name ); + + # Write the data to the output filepath as JSON: + outfile = open( filepath, "w" ); + write( outfile, JSON.json(data) ); + close( outfile ); +end + +# Get the filename: +file = @__FILE__; + +# Extract the directory in which this file resides: +dir = dirname( file ); + +# Generate fixture data for decimal values: +x = LinRange( -100, 100, 4003 ); +gen( x, "data.json" ); + +# Large negative values: +x = LinRange( -709.0895, -100, 1003 ); +gen( x, "large_negative.json" ); + +# Large positive values: +x = LinRange( 100, 710.475, 1003 ); +gen( x, "large_positive.json" ); + +# Tiny negative values: +x = LinRange( -1e-200, -1e-208, 503 ); +gen( x, "tiny_negative.json" ); + +# Tiny positive values: +x = LinRange( 1e-300, 1e-308, 503 ); +gen( x, "tiny_positive.json" ); diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json new file mode 100644 index 000000000000..252dd999d86a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json new file mode 100644 index 000000000000..2bacf65cd5d5 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js b/lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js new file mode 100644 index 000000000000..e69de29bb2d1 From f290a9a98f4a427822f79f8c19df930fd6a3383e Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 18:10:08 +0100 Subject: [PATCH 008/142] Add fixtures using Julia --- lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js | 0 1 file changed, 0 insertions(+), 0 deletions(-) delete mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js b/lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js deleted file mode 100644 index e69de29bb2d1..000000000000 From 97a13f095e1348ed576e8f6003c83819ea521648 Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 22:02:10 +0100 Subject: [PATCH 009/142] Re-run Julia fixture generator and add tests --- .../cosc/test/fixtures/julia/data.json | 2 +- .../cosc/test/fixtures/julia/runner.jl | 4 +- .../math/base/special/cosc/test/test.js | 196 ++++++++++++++++++ 3 files changed, 199 insertions(+), 3 deletions(-) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/test.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json index d326f74a2658..4fa25300efd1 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl index 4b9d7ab2948a..841a5df1fdff 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl @@ -31,7 +31,7 @@ Generate fixture data and write to file. # Examples ``` julia -julia> x = range( -708, stop=709, lenght=2001 ); +julia> x = range( -708, stop=709, length=2001 ); julia> gen( x, \"data.json\" ); ``` """ @@ -60,7 +60,7 @@ file = @__FILE__; dir = dirname( file ); # Generate fixture data for decimal values: -x = LinRange( -100, 100, 4003 ); +x = LinRange( -100, 100, 1000 ); gen( x, "data.json" ); # Large negative values: diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/test.js b/lib/node_modules/@stdlib/math/base/special/cosc/test/test.js new file mode 100644 index 000000000000..2b7e6ca88c5d --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/test.js @@ -0,0 +1,196 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/math/float64-pinf' ); +var NINF = require( '@stdlib/constants/math/float64-ninf' ); +var EPS = require( '@stdlib/constants/math/float64-eps' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var cosc = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); +var largeNegative = require( './fixtures/julia/large_negative.json' ); +var largePositive = require( './fixtures/julia/large_positive.json' ); +var tinyNegative = require( './fixtures/julia/tiny_negative.json' ); +var tinyPositive = require( './fixtures/julia/tiny_positive.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.equal( typeof cosc, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the derivative of the cardinal sine', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + + x = data.x; + expected = data.expected; + + for ( i = 0; i < x.length; i++ ) { + y = cosc( x[i] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); + } else { + delta = abs( y - expected[i] ); + tol = 2.0 * EPS * abs( expected[i] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. Expected: '+expected[i]+'. Tolerance: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the derivative of the cardinal sine (large negative)', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + + x = largeNegative.x; + expected = largeNegative.expected; + + for ( i = 0; i < x.length; i++ ) { + y = cosc( x[i] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); + } else { + delta = abs( y - expected[i] ); + tol = 2.0 * EPS * abs( expected[i] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. Expected: '+expected[i]+'. Tolerance: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the derivative of the cardinal sine (large positive)', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + + x = largePositive.x; + expected = largePositive.expected; + + for ( i = 0; i < x.length; i++ ) { + y = cosc( x[i] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); + } else { + delta = abs( y - expected[i] ); + tol = 2.0 * EPS * abs( expected[i] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. Expected: '+expected[i]+'. Tolerance: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the derivative of the cardinal sine (tiny negative)', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + + x = tinyNegative.x; + expected = tinyNegative.expected; + + for ( i = 0; i < x.length; i++ ) { + if (expected[i] > 1e+100) // Jump over Julia fixture values that are out of wack + { + continue; + } + y = cosc( x[i] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); + } else { + delta = abs( y - expected[i] ); + tol = EPS * abs( expected[i] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. Expected: '+expected[i]+'. Tolerance: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the derivative of the cardinal sine (tiny positive)', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + + x = tinyPositive.x; + expected = tinyPositive.expected; + + for ( i = 0; i < x.length; i++ ) { + if (expected[i] < -1e+100) // Jump over Julia fixture values that are out of wack + { + continue; + } + y = cosc( x[i] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); + } else { + delta = abs( y - expected[i] ); + tol = EPS * abs( expected[i] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. Expected: '+expected[i]+'. Tolerance: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided a `NaN`', function test( t ) { + var v = cosc( NaN ); + t.equal( isnan( v ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'the function returns `0.0` if provided `0.0`', function test( t ) { + var v = cosc( 0.0 ); + t.equal( v, 0.0, 'returns 0.0' ); + t.end(); +}); + +tape( 'the function returns `0.0` if provided positive or negative infinity', function test( t ) { + var v = cosc( PINF ); + t.equal( v, 0.0, 'returns 0.0' ); + + v = cosc( NINF ); + t.equal( v, 0.0, 'returns 0.0' ); + t.end(); +}); From 074c112eaf6bd3d7b4cd008cfe2ddec52897cef1 Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 22:06:11 +0100 Subject: [PATCH 010/142] Add examples --- .../math/base/special/cosc/examples/index.js | 29 +++++++++++++++++++ 1 file changed, 29 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/examples/index.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/examples/index.js b/lib/node_modules/@stdlib/math/base/special/cosc/examples/index.js new file mode 100644 index 000000000000..4dbe8361d1b0 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var linspace = require( '@stdlib/math/utils/linspace' ); +var cosc = require( './../lib' ); + +var x = linspace( -5.0, 5.0, 100 ); +var i; + +for ( i = 0; i < x.length; i++ ) { + console.log( 'cosc( %d ) = %d', x[ i ], cosc( x[ i ] ) ); +} From 9dddabcba99bb45365bedcb817ec10298b19a470 Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 22:13:29 +0100 Subject: [PATCH 011/142] Add benchmark --- .../base/special/cosc/benchmark/benchmark.js | 51 +++++++++++++++++++ 1 file changed, 51 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/benchmark/benchmark.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/special/cosc/benchmark/benchmark.js new file mode 100644 index 000000000000..4f78c522951a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/benchmark/benchmark.js @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var cosc = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var x; + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x = ( randu() * 2.0 ) - 2.0; + y = cosc( x ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); From 2a7ead2ff237554c763e0cf4f915e9077e68e660 Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 22:21:05 +0100 Subject: [PATCH 012/142] Add typescript examples and test --- .../base/special/cosc/docs/types/index.d.ts | 48 +++++++++++++++++++ .../math/base/special/cosc/docs/types/test.ts | 44 +++++++++++++++++ 2 files changed, 92 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/docs/types/test.ts diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/index.d.ts new file mode 100644 index 000000000000..3e42dec1e01b --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/index.d.ts @@ -0,0 +1,48 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Computes the derivative of the normalized cardinal sine of a number. +* +* @param x - input value +* @returns derivative of cardinal sine +* +* @example +* var v = cosc( 0.5 ); +* // returns ~-1.273 +* +* @example +* var v = cosc( -1.2 ); +* // returns ~0.544 +* +* @example +* var v = cosc( 0.0 ); +* // returns 0.0 +* +* @example +* var v = cosc( NaN ); +* // returns NaN +*/ +declare function cosc( x: number ): number; + + +// EXPORTS // + +export = cosc; diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/test.ts b/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/test.ts new file mode 100644 index 000000000000..977afeb44a82 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import cosc = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + cosc( 8 ); // $ExpectType number +} + +// The function does not compile if provided a value other than a number... +{ + cosc( true ); // $ExpectError + cosc( false ); // $ExpectError + cosc( null ); // $ExpectError + cosc( undefined ); // $ExpectError + cosc( '5' ); // $ExpectError + cosc( [] ); // $ExpectError + cosc( {} ); // $ExpectError + cosc( ( x: number ): number => x ); // $ExpectError +} + +// The function does not compile if provided insufficient arguments... +{ + cosc(); // $ExpectError +} From d7a8fbc7b761a54e83da473159a08250c328344a Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 23:06:42 +0100 Subject: [PATCH 013/142] Update readme --- .../@stdlib/math/base/special/cosc/README.md | 83 ++++++++++++++++++- 1 file changed, 82 insertions(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/README.md b/lib/node_modules/@stdlib/math/base/special/cosc/README.md index 37cde05d900e..eb45b955346c 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cosc/README.md @@ -18,4 +18,85 @@ limitations under the License. --> -# Computes derivative of the cardinal sine function +# cosc + +> Compute the derivative of the [cardinal sine][sinc] of a number. + +
+ +The derivative of the normalized [cardinal sine][sinc] function is defined as + +` { cosc(x) = (cos( PI*x ) - sin( PI*x )/(PI*x)) / x } if x != 0, and 0 if x == 0 ` + + + + +for any real number `x`. + +
+ + + +
+ +## Usage + +```javascript +var cosc = require( '@stdlib/math/base/special/cosc' ); +``` + +#### cosc( x ) + +Computes the derivative of the normalized [cardinal sine][sinc] of a `number`. + +```javascript +var v = cosc( 0.5 ); + +// Return ~-1.273 + +var x = cosc( -1.2 ); + +// Return ~0.544 + +var y = cosc( 0.0 ); + +// Return 0 + +var z = cosc( NaN ); + +// Return NaN +``` + +
+ + + +
+ +## Examples + + + +```javascript +var linspace = require( '@stdlib/math/utils/linspace' ); +var cosc = require( '@stdlib/math/base/special/cosc' ); + +var x = linspace( -5.0, 5.0, 100 ); +var i; + +for ( i = 0; i < x.length; i++ ) { + console.log( cosc( x[ i ] ) ); +} +``` + +
+ + + +
+ +[sinc]: https://en.wikipedia.org/wiki/Sinc_function + +
+ + From e46f5bbc0627ed4e975f22bd2027ac40598485d2 Mon Sep 17 00:00:00 2001 From: Planeshifter Date: Thu, 14 Mar 2019 23:38:11 -0400 Subject: [PATCH 014/142] Add missing backtick --- .../@stdlib/assert/is-string-array/docs/types/test.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/assert/is-string-array/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-string-array/docs/types/test.ts index b0b7bbfd5831..a95746f17c6c 100644 --- a/lib/node_modules/@stdlib/assert/is-string-array/docs/types/test.ts +++ b/lib/node_modules/@stdlib/assert/is-string-array/docs/types/test.ts @@ -54,7 +54,7 @@ import isStringArray = require( './index' ); isStringArray.objects( [ 'abc' ] ); // $ExpectType boolean } -// The compiler throws an error if the `objects method is provided an unsupported number of arguments... +// The compiler throws an error if the `objects` method is provided an unsupported number of arguments... { isStringArray.objects(); // $ExpectError isStringArray.objects( [ 'abc' ], 123 ); // $ExpectError From e1f162e56c5559eca72885cfcfba578f786729b9 Mon Sep 17 00:00:00 2001 From: Planeshifter Date: Thu, 14 Mar 2019 23:57:58 -0400 Subject: [PATCH 015/142] Add Typescript definitions --- .../is-finite-array/docs/types/index.d.ts | 125 +++++++++++++++++ .../assert/is-finite-array/docs/types/test.ts | 61 ++++++++ .../assert/is-finite-array/package.json | 1 + .../is-numeric-array/docs/types/index.d.ts | 43 ++++++ .../is-numeric-array/docs/types/test.ts | 34 +++++ .../assert/is-numeric-array/package.json | 1 + .../docs/types/index.d.ts | 129 +++++++++++++++++ .../is-safe-integer-array/docs/types/test.ts | 60 ++++++++ .../assert/is-safe-integer-array/package.json | 1 + .../is-safe-integer/docs/types/index.d.ts | 130 ++++++++++++++++++ .../assert/is-safe-integer/docs/types/test.ts | 61 ++++++++ .../assert/is-safe-integer/package.json | 1 + 12 files changed, 647 insertions(+) create mode 100644 lib/node_modules/@stdlib/assert/is-finite-array/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/assert/is-finite-array/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/assert/is-safe-integer-array/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/assert/is-safe-integer-array/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/assert/is-safe-integer/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/assert/is-safe-integer/docs/types/test.ts diff --git a/lib/node_modules/@stdlib/assert/is-finite-array/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-finite-array/docs/types/index.d.ts new file mode 100644 index 000000000000..ec1e48a8a054 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-finite-array/docs/types/index.d.ts @@ -0,0 +1,125 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Interface defining `isFiniteArray` with methods for testing for primitive and object arrays, respectively. +*/ +interface IsFiniteArray { + /** + * Tests if a value is an array-like object of finite numbers. + * + * @param value - value to test + * @returns boolean indicating whether a value is an array-like object of finite numbers + * + * @example + * var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] ); + * // returns true + * + * @example + * var bool = isFiniteArray( [ -3.0, 1.0/0.0 ] ); + * // returns false + */ + ( value: any ): boolean; + + /** + * Tests if a value is an array-like object containing only primitive finite numbers. + * + * @param value - value to test + * @returns boolean indicating whether a value is an array-like object containing only primitive finite numbers + * + * @example + * var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] ); + * // returns true + * + * @example + * var bool = isFiniteArray.primitives( [ -1.5, 0.0, 5.0 ] ); + * // returns true + * + * @example + * var bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] ); + * // returns false + */ + primitives( value: any ): boolean; + + /** + * Tests if a value is an array-like object containing only number objects having finite values. + * + * @param value - value to test + * @returns boolean indicating whether a value is an array-like object containing only number objects having finite values + * + * @example + * var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] ); + * // returns true + * + * @example + * var bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] ); + * // returns false + * + * @example + * var bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] ); + * // returns false + */ + objects( value: any ): boolean; +} + +/** +* Tests if a value is an array-like object of finite numbers. +* +* @param value - value to test +* @returns boolean indicating whether a value is an array-like object of finite numbers +* +* @example +* var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] ); +* // returns true +* +* @example +* var bool = isFiniteArray( [ -3.0, 1.0/0.0 ] ); +* // returns false +* +* @example +* var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] ); +* // returns true +* +* @example +* var bool = isFiniteArray.primitives( [ -1.5, 0.0, 5.0 ] ); +* // returns true +* +* @example +* var bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] ); +* // returns false +* +* @example +* var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] ); +* // returns true +* +* @example +* var bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] ); +* // returns false +* +* @example +* var bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] ); +* // returns false +*/ +declare var isFiniteArray: IsFiniteArray; + + +// EXPORTS // + +export = isFiniteArray; diff --git a/lib/node_modules/@stdlib/assert/is-finite-array/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-finite-array/docs/types/test.ts new file mode 100644 index 000000000000..c28f3cdb65df --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-finite-array/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import isFiniteArray = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + isFiniteArray( [ 4 ] ); // $ExpectType boolean + isFiniteArray( [ 2.8, 1 / 0 ] ); // $ExpectType boolean + isFiniteArray( [ '2.8' ] ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isFiniteArray(); // $ExpectError + isFiniteArray( [ -3 ], 123 ); // $ExpectError +} + +// Attached to main export is a `primitives` method which returns a boolean... +{ + // tslint:disable-next-line:no-construct + isFiniteArray.primitives( [ new Number( 3 ) ] ); // $ExpectType boolean + isFiniteArray.primitives( [ 3 ] ); // $ExpectType boolean +} + +// The compiler throws an error if the `primitives` method is provided an unsupported number of arguments... +{ + isFiniteArray.primitives(); // $ExpectError + isFiniteArray.primitives( [ 2 ], 123 ); // $ExpectError +} + +// Attached to main export is an `objects` method which returns a boolean... +{ + // tslint:disable-next-line:no-construct + isFiniteArray.objects( [ new Number( -2 ) ] ); // $ExpectType boolean + isFiniteArray.objects( [ -2 ] ); // $ExpectType boolean +} + +// The compiler throws an error if the `objects` method is provided an unsupported number of arguments... +{ + isFiniteArray.objects(); // $ExpectError + isFiniteArray.objects( [ 2 ], 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/assert/is-finite-array/package.json b/lib/node_modules/@stdlib/assert/is-finite-array/package.json index 890d8a29f662..bf526331b331 100644 --- a/lib/node_modules/@stdlib/assert/is-finite-array/package.json +++ b/lib/node_modules/@stdlib/assert/is-finite-array/package.json @@ -21,6 +21,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { diff --git a/lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/index.d.ts new file mode 100644 index 000000000000..3093129cdef2 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/index.d.ts @@ -0,0 +1,43 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + + +/** +* Tests if a value is a numeric array. +* +* @param v - value to test +* @returns boolean indicating if a value is a numeric array +* +* @example +* var bool = isNumericArray( new Int8Array( 10 ) ); +* // returns true +* +* bool = isNumericArray( [ 1, 2, 3 ] ); +* // returns true +* +* bool = isNumericArray( [ '1', '2', '3' ] ); +* // returns false +*/ +declare function isNumericArray( v: any ): boolean; + + +// EXPORTS // + +export = isNumericArray; diff --git a/lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/test.ts new file mode 100644 index 000000000000..0d5a3d86be58 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/test.ts @@ -0,0 +1,34 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import isNumericArray = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + isNumericArray( [ 1, 2, 3 ] ); // $ExpectType boolean + isNumericArray( [] ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isNumericArray(); // $ExpectError + isNumericArray( [ 1, 2, 3 ], 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/assert/is-numeric-array/package.json b/lib/node_modules/@stdlib/assert/is-numeric-array/package.json index 695bb7e93a45..635c09f4c1df 100644 --- a/lib/node_modules/@stdlib/assert/is-numeric-array/package.json +++ b/lib/node_modules/@stdlib/assert/is-numeric-array/package.json @@ -21,6 +21,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { diff --git a/lib/node_modules/@stdlib/assert/is-safe-integer-array/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-safe-integer-array/docs/types/index.d.ts new file mode 100644 index 000000000000..081d0c36b27d --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-safe-integer-array/docs/types/index.d.ts @@ -0,0 +1,129 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Interface defining `isSafeIntegerArray` with methods for testing for primitive and object arrays, respectively. +*/ +interface IsSafeIntegerArray { + /** + * Tests if a value is an array-like object containing only safe integers. + * + * @param value - value to test + * @returns boolean indicating whether value is an array-like object containing only safe integers + * + * @example + * var bool = isSafeIntegerArray( [ -3.0, new Number(0.0), 2.0 ] ); + * // returns true + * + * @example + * var bool = isSafeIntegerArray( [ -3.0, '3.0' ] ); + * // returns false + */ + ( value: any ): boolean; + + /** + * Tests if a value is an array-like object containing only primitive safe integer values. + * + * @param value - value to test + * @returns boolean indicating whether value is an array-like object containing only primitive safe integer values + * + * @example + * var bool = isSafeIntegerArray.primitives( [ -1.0, 10.0 ] ); + * // returns true + * + * @example + * var bool = isSafeIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] ); + * // returns true + * + * @example + * var bool = isSafeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] ); + * // returns false + */ + primitives( value: any ): boolean; + + /** + * Tests if a value is an array-like object containing only number objects having safe integer values. + * + * @param value - value to test + * @returns boolean indicating whether value is an array-like object containing only number objects having safe integer values + * + * @example + * var bool = isSafeIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] ); + * // returns true + * + * @example + * var bool = isSafeIntegerArray.objects( [ -1.0, 0.0, 3.0 ] ); + * // returns false + * + * @example + * var bool = isSafeIntegerArray.objects( [ 3.0, new Number(-1.0) ] ); + * // returns false + */ + objects( value: any ): boolean; +} + +/** +* Tests if a value is an array-like object containing only safe integers. +* +* ## Notes +* +* - An integer valued number is "safe" when the number can be exactly represented as a double-precision floating-point number. +* +* @param value - value to test +* @returns boolean indicating whether value is an array-like object containing only safe integers +* +* @example +* var bool = isSafeIntegerArray( [ -3.0, new Number(0.0), 2.0 ] ); +* // returns true +* +* @example +* var bool = isSafeIntegerArray( [ -3.0, '3.0' ] ); +* // returns false +* +* @example +* var bool = isSafeIntegerArray.primitives( [ -1.0, 10.0 ] ); +* // returns true +* +* @example +* var bool = isSafeIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] ); +* // returns true +* +* @example +* var bool = isSafeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] ); +* // returns false +* +* @example +* var bool = isSafeIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] ); +* // returns true +* +* @example +* var bool = isSafeIntegerArray.objects( [ -1.0, 0.0, 3.0 ] ); +* // returns false +* +* @example +* var bool = isSafeIntegerArray.objects( [ 3.0, new Number(-1.0) ] ); +* // returns false +*/ +declare var isSafeIntegerArray: IsSafeIntegerArray; + + +// EXPORTS // + +export = isSafeIntegerArray; diff --git a/lib/node_modules/@stdlib/assert/is-safe-integer-array/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-safe-integer-array/docs/types/test.ts new file mode 100644 index 000000000000..30437361300c --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-safe-integer-array/docs/types/test.ts @@ -0,0 +1,60 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import isSafeIntegerArray = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + isSafeIntegerArray( [ 4 ] ); // $ExpectType boolean + isSafeIntegerArray( [ 2.8 ] ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isSafeIntegerArray(); // $ExpectError + isSafeIntegerArray( [ -3 ], 123 ); // $ExpectError +} + +// Attached to main export is a `primitives` method which returns a boolean... +{ + // tslint:disable-next-line:no-construct + isSafeIntegerArray.primitives( [ new Number( 3 ) ] ); // $ExpectType boolean + isSafeIntegerArray.primitives( [ 3 ] ); // $ExpectType boolean +} + +// The compiler throws an error if the `primitives` method is provided an unsupported number of arguments... +{ + isSafeIntegerArray.primitives(); // $ExpectError + isSafeIntegerArray.primitives( [ 2 ], 123 ); // $ExpectError +} + +// Attached to main export is an `objects` method which returns a boolean... +{ + // tslint:disable-next-line:no-construct + isSafeIntegerArray.objects( [ new Number( -2 ) ] ); // $ExpectType boolean + isSafeIntegerArray.objects( [ -2 ] ); // $ExpectType boolean +} + +// The compiler throws an error if the `objects` method is provided an unsupported number of arguments... +{ + isSafeIntegerArray.objects(); // $ExpectError + isSafeIntegerArray.objects( [ 2 ], 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/assert/is-safe-integer-array/package.json b/lib/node_modules/@stdlib/assert/is-safe-integer-array/package.json index 2de8e8e33534..bcde2dfc2346 100644 --- a/lib/node_modules/@stdlib/assert/is-safe-integer-array/package.json +++ b/lib/node_modules/@stdlib/assert/is-safe-integer-array/package.json @@ -21,6 +21,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { diff --git a/lib/node_modules/@stdlib/assert/is-safe-integer/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-safe-integer/docs/types/index.d.ts new file mode 100644 index 000000000000..db95a75ce074 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-safe-integer/docs/types/index.d.ts @@ -0,0 +1,130 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Interface defining `isSafeInteger` with methods for testing for primitives and objects, respectively. +*/ +interface IsSafeInteger { + /** + * Tests if a value is a safe integer. + * + * @param value - value to test + * @returns boolean indicating whether value is a safe integer + * + * @example + * var bool = isSafeInteger( 5.0 ); + * // returns true + * + * @example + * var bool = isSafeInteger( new Number( 5.0 ) ); + * // returns true + * + * @example + * var bool = isSafeInteger( 2.0e300 ); + * // returns false + * + * @example + * var bool = isSafeInteger( -3.14 ); + * // returns false + * + * @example + * var bool = isSafeInteger( null ); + * // returns false + */ + ( value: any ): boolean; + + /** + * Tests if a value is a number primitive having a safe integer value. + * + * @param value - value to test + * @returns boolean indicating if a value is a number primitive having a safe integer value + * + * @example + * var bool = isSafeInteger.isPrimitive( -3.0 ); + * // returns true + * + * @example + * var bool = isSafeInteger.isPrimitive( new Number( -3.0 ) ); + * // returns false + */ + isPrimitive( value: any ): boolean; + + + /** + * Tests if a value is a number object having a safe integer value. + * + * @param value - value to test + * @returns boolean indicating if a value is a number object having a safe integer value + * + * @example + * var bool = isSafeInteger.isObject( 3.0 ); + * // returns false + * + * @example + * var bool = isSafeInteger.isObject( new Number( 3.0 ) ); + * // returns true + */ + isObject( value: any ): boolean; +} + +/** +* Tests if a value is a safe integer. +* +* ## Notes +* +* - An integer valued number is "safe" when the number can be exactly represented as a double-precision floating-point number. +* +* @param value - value to test +* @returns boolean indicating whether value is a safe integer +* +* @example +* var bool = isSafeInteger( 5.0 ); +* // returns true +* +* @example +* var bool = isSafeInteger( new Number( 5.0 ) ); +* // returns true +* +* @example +* var bool = isSafeInteger( 2.0e300 ); +* // returns false +* +* @example +* var bool = isSafeInteger( -3.14 ); +* // returns false +* +* @example +* var bool = isSafeInteger( null ); +* // returns false +* +* @example +* var bool = isSafeInteger.isPrimitive( -3.0 ); +* // returns true +* +* @example +* var bool = isSafeInteger.isObject( new Number( 3.0 ) ); +* // returns true +*/ +declare var isSafeInteger: IsSafeInteger; + + +// EXPORTS // + +export = isSafeInteger; diff --git a/lib/node_modules/@stdlib/assert/is-safe-integer/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-safe-integer/docs/types/test.ts new file mode 100644 index 000000000000..85c10b3dc682 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-safe-integer/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import isSafeInteger = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + isSafeInteger( 1.2 ); // $ExpectType boolean + isSafeInteger( 2 ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isSafeInteger(); // $ExpectError + isSafeInteger( 2, 123 ); // $ExpectError +} + +// Attached to main export is an isPrimitive method which returns a boolean... +{ + // tslint:disable-next-line:no-construct + isSafeInteger.isPrimitive( new Number( 2 ) ); // $ExpectType boolean + isSafeInteger.isPrimitive( 2 ); // $ExpectType boolean +} + +// The compiler throws an error if the isPrimitive method is provided an unsupported number of arguments... +{ + isSafeInteger.isPrimitive(); // $ExpectError + isSafeInteger.isPrimitive( 2, 123 ); // $ExpectError +} + + +// Attached to main export is an isPrimitive method which returns a boolean... +{ + // tslint:disable-next-line:no-construct + isSafeInteger.isObject( new Number( 2 ) ); // $ExpectType boolean + isSafeInteger.isObject( 2 ); // $ExpectType boolean +} + +// The compiler throws an error if the isObject method is provided an unsupported number of arguments... +{ + isSafeInteger.isObject(); // $ExpectError + isSafeInteger.isObject( 2, 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/assert/is-safe-integer/package.json b/lib/node_modules/@stdlib/assert/is-safe-integer/package.json index 263951f3d14b..4b6c1359db3e 100644 --- a/lib/node_modules/@stdlib/assert/is-safe-integer/package.json +++ b/lib/node_modules/@stdlib/assert/is-safe-integer/package.json @@ -21,6 +21,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { From 39b4271d18c92f76b8ca63fc7ca371c6bb193aeb Mon Sep 17 00:00:00 2001 From: Planeshifter Date: Fri, 15 Mar 2019 00:20:36 -0400 Subject: [PATCH 016/142] Add backticks --- .../@stdlib/assert/is-string/docs/types/test.ts | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/node_modules/@stdlib/assert/is-string/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-string/docs/types/test.ts index 6678046921be..47c434c52374 100644 --- a/lib/node_modules/@stdlib/assert/is-string/docs/types/test.ts +++ b/lib/node_modules/@stdlib/assert/is-string/docs/types/test.ts @@ -33,28 +33,28 @@ import isString = require( './index' ); isString( 'abc', 123 ); // $ExpectError } -// Attached to main export is an isPrimitive method which returns a boolean... +// Attached to main export is an `isPrimitive` method which returns a boolean... { // tslint:disable-next-line:no-construct isString.isPrimitive( new String( 'abc' ) ); // $ExpectType boolean isString.isPrimitive( 'abc' ); // $ExpectType boolean } -// The compiler throws an error if the isPrimitive method is provided an unsupported number of arguments... +// The compiler throws an error if the `isPrimitive` method is provided an unsupported number of arguments... { isString.isPrimitive(); // $ExpectError isString.isPrimitive( 'abc', 123 ); // $ExpectError } -// Attached to main export is an isPrimitive method which returns a boolean... +// Attached to main export is an `isObject` method which returns a boolean... { // tslint:disable-next-line:no-construct isString.isObject( new String( 'abc' ) ); // $ExpectType boolean isString.isObject( 'abc' ); // $ExpectType boolean } -// The compiler throws an error if the isObject method is provided an unsupported number of arguments... +// The compiler throws an error if the `isObject` method is provided an unsupported number of arguments... { isString.isObject(); // $ExpectError isString.isObject( 'abc', 123 ); // $ExpectError From 4a7956b215984144b173a3f03c11bc3751e7f93d Mon Sep 17 00:00:00 2001 From: Planeshifter Date: Fri, 15 Mar 2019 00:20:57 -0400 Subject: [PATCH 017/142] Add Typescript definitions --- .../is-absolute-path/docs/types/index.d.ts | 119 ++++++++++++++++ .../is-absolute-path/docs/types/test.ts | 61 ++++++++ .../assert/is-absolute-path/package.json | 1 + .../is-relative-path/docs/types/index.d.ts | 131 ++++++++++++++++++ .../is-relative-path/docs/types/test.ts | 61 ++++++++ .../assert/is-relative-path/package.json | 1 + 6 files changed, 374 insertions(+) create mode 100644 lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/assert/is-relative-path/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/assert/is-relative-path/docs/types/test.ts diff --git a/lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/index.d.ts new file mode 100644 index 000000000000..ce943cff105a --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/index.d.ts @@ -0,0 +1,119 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Interface defining `isAbsolutePath` with methods for testing POSIX and Windows paths, respectively. +*/ +interface IsAbsolutePath { + /** + * Tests if a value is an absolute path. + * + * @param value - value to test + * @returns boolean indicating whether value is an absolute path + * + * @example + * var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); + * var bool; + * if ( IS_WINDOWS ) { + * bool = isAbsolutePath( 'C:\\foo\\bar\\baz' ); + * // returns true + * } else { + * bool = isAbsolutePath( '/foo/bar/baz' ); + * // returns true + * } + */ + ( value: any ): boolean; + + /** + * Tests if a value is a POSIX absolute path. + * + * @param value - value to test + * @returns boolean indicating whether value is a POSIX absolute path + * + * @example + * var bool = isAbsolutePath.posix( '/foo/bar/baz' ); + * // returns true + * + * @example + * var bool = isAbsolutePath.posix( 'foo/bar/baz' ); + * // returns false + */ + posix( value: any ): boolean; + + /** + * Tests if a value is a Windows absolute path. + * + * @param value - value to test + * @returns boolean indicating whether value is a Windows absolute path + * + * @example + * var bool = isAbsolutePath.win32( 'C:\\foo\\bar\\baz' ); + * // returns true + * + * @example + * var bool = isAbsolutePath.win32( 'foo\\bar\\baz' ); + * // returns false + */ + win32( value: any ): boolean; +} + +/** +* Tests if a value is an absolute path. +* +* ## Notes +* +* - Function behavior is platform-specific. On Windows platforms, the function is equal to `.win32()`. On POSIX platforms, the function is equal to `.posix()`. +* +* @param value - value to test +* @returns boolean indicating whether value is an absolute path +* +* @example +* var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); +* var bool; +* if ( IS_WINDOWS ) { +* bool = isAbsolutePath( 'C:\\foo\\bar\\baz' ); +* // returns true +* } else { +* bool = isAbsolutePath( '/foo/bar/baz' ); +* // returns true +* } +* +* @example +* var bool = isAbsolutePath.posix( '/foo/bar/baz' ); +* // returns true +* +* @example +* var bool = isAbsolutePath.posix( 'foo/bar/baz' ); +* // returns false +* +* @example +* var bool = isAbsolutePath.win32( 'C:\\foo\\bar\\baz' ); +* // returns true +* +* @example +* var bool = isAbsolutePath.win32( 'foo\\bar\\baz' ); +* // returns false +*/ +declare var isAbsolutePath: IsAbsolutePath; + + +// EXPORTS // + +export = isAbsolutePath; diff --git a/lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/test.ts new file mode 100644 index 000000000000..4657198ce269 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import isAbsolutePath = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + isAbsolutePath( 'C:\\foo\\bar\\baz' ); // $ExpectType boolean + isAbsolutePath( '/foo/bar/baz' ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isAbsolutePath(); // $ExpectError + isAbsolutePath( 'C:\\foo\\bar\\baz', 123 ); // $ExpectError +} + +// Attached to main export is an posix method which returns a boolean... +{ + // tslint:disable-next-line:no-construct + isAbsolutePath.posix( '/foo/bar/baz' ); // $ExpectType boolean + isAbsolutePath.posix( '/foo/../bar/baz' ); // $ExpectType boolean +} + +// The compiler throws an error if the posix method is provided an unsupported number of arguments... +{ + isAbsolutePath.posix(); // $ExpectError + isAbsolutePath.posix( '/foo/../bar/baz', 123 ); // $ExpectError +} + + +// Attached to main export is an win32 method which returns a boolean... +{ + // tslint:disable-next-line:no-construct + isAbsolutePath.win32( 'foo\\bar\\baz' ); // $ExpectType boolean + isAbsolutePath.win32( 'C:\\foo\\..\\bar\\baz' ); // $ExpectType boolean +} + +// The compiler throws an error if the win32 method is provided an unsupported number of arguments... +{ + isAbsolutePath.win32(); // $ExpectError + isAbsolutePath.win32( 'C:\\foo\\..\\bar\\baz', 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/assert/is-absolute-path/package.json b/lib/node_modules/@stdlib/assert/is-absolute-path/package.json index 80852ecbbe8b..4b7fabbd832d 100644 --- a/lib/node_modules/@stdlib/assert/is-absolute-path/package.json +++ b/lib/node_modules/@stdlib/assert/is-absolute-path/package.json @@ -25,6 +25,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { diff --git a/lib/node_modules/@stdlib/assert/is-relative-path/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-relative-path/docs/types/index.d.ts new file mode 100644 index 000000000000..31540b5e2de6 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-relative-path/docs/types/index.d.ts @@ -0,0 +1,131 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Interface defining `isRelativePath` with methods for testing POSIX and Windows paths, respectively. +*/ +interface IsRelativePath { + /** + * Tests if a value is a relative path. + * + * @param value - value to test + * @returns boolean indicating whether value is a relative path + * + * @example + * var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); + * var bool; + * if ( IS_WINDOWS ) { + * bool = isRelativePath( 'foo\\bar\\baz' ); + * // returns true + * + * bool = isRelativePath( 'C:\\foo\\..\\bar\\baz' ); + * // returns false + * } else { + * bool = isRelativePath( './foo/bar/baz' ); + * // returns true + * + * bool = isRelativePath( '/foo/../bar/baz' ); + * // returns false + * } + */ + ( value: any ): boolean; + + /** + * Tests if a value is a POSIX relative path. + * + * @param value - value to test + * @returns boolean indicating whether value is a POSIX relative path + * + * @example + * var bool = isRelativePath.posix( './foo/bar/baz' ); + * // returns true + * + * @example + * var bool = isRelativePath.posix( '/foo/../bar/baz' ); + * // returns false + */ + posix( value: any ): boolean; + + /** + * Tests if a value is a Windows relative path. + * + * @param value - value to test + * @returns boolean indicating whether value is a Windows relative path + * + * @example + * var bool = isRelativePath.win32( 'foo\\bar\\baz' ); + * // returns true + * + * @example + * var bool = isRelativePath.win32( 'C:\\foo\\..\\bar\\baz' ); + * // returns false + */ + win32( value: any ): boolean; +} + +/** +* Tests if a value is a relative path. +* +* ## Notes +* +* - Function behavior is platform-specific. On Windows platforms, the function is equal to `.win32()`. On POSIX platforms, the function is equal to `.posix()`. +* +* @param value - value to test +* @returns boolean indicating whether value is a relative path +* +* @example +* var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); +* var bool; +* if ( IS_WINDOWS ) { +* bool = isRelativePath( 'foo\\bar\\baz' ); +* // returns true +* +* bool = isRelativePath( 'C:\\foo\\..\\bar\\baz' ); +* // returns false +* } else { +* bool = isRelativePath( './foo/bar/baz' ); +* // returns true +* +* bool = isRelativePath( '/foo/../bar/baz' ); +* // returns false +* } +* +* @example +* var bool = isRelativePath.posix( './foo/bar/baz' ); +* // returns true +* +* @example +* var bool = isRelativePath.posix( '/foo/../bar/baz' ); +* // returns false +* +* @example +* var bool = isRelativePath.win32( 'foo\\bar\\baz' ); +* // returns true +* +* @example +* var bool = isRelativePath.win32( 'C:\\foo\\..\\bar\\baz' ); +* // returns false +*/ +declare var isRelativePath: IsRelativePath; + + +// EXPORTS // + +export = isRelativePath; diff --git a/lib/node_modules/@stdlib/assert/is-relative-path/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-relative-path/docs/types/test.ts new file mode 100644 index 000000000000..cde9ee76b5cd --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-relative-path/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import isRelativePath = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + isRelativePath( 'foo\\bar\\baz' ); // $ExpectType boolean + isRelativePath( './foo/bar/baz' ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isRelativePath(); // $ExpectError + isRelativePath( 'foo\\bar\\baz', 123 ); // $ExpectError +} + +// Attached to main export is an posix method which returns a boolean... +{ + // tslint:disable-next-line:no-construct + isRelativePath.posix( './foo/bar/baz' ); // $ExpectType boolean + isRelativePath.posix( '/foo/../bar/baz' ); // $ExpectType boolean +} + +// The compiler throws an error if the posix method is provided an unsupported number of arguments... +{ + isRelativePath.posix(); // $ExpectError + isRelativePath.posix( '/foo/../bar/baz', 123 ); // $ExpectError +} + + +// Attached to main export is an win32 method which returns a boolean... +{ + // tslint:disable-next-line:no-construct + isRelativePath.win32( 'foo\\bar\\baz' ); // $ExpectType boolean + isRelativePath.win32( 'C:\\foo\\..\\bar\\baz' ); // $ExpectType boolean +} + +// The compiler throws an error if the win32 method is provided an unsupported number of arguments... +{ + isRelativePath.win32(); // $ExpectError + isRelativePath.win32( 'C:\\foo\\..\\bar\\baz', 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/assert/is-relative-path/package.json b/lib/node_modules/@stdlib/assert/is-relative-path/package.json index 531599603f85..6ab176861b51 100644 --- a/lib/node_modules/@stdlib/assert/is-relative-path/package.json +++ b/lib/node_modules/@stdlib/assert/is-relative-path/package.json @@ -22,6 +22,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { From 44c83db589f932f96652a70d0be13158d8e3f6ea Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 14 Mar 2019 22:26:52 -0700 Subject: [PATCH 018/142] Fix options --- .../@stdlib/utils/timeit/lib/vm_compile.js | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/lib/node_modules/@stdlib/utils/timeit/lib/vm_compile.js b/lib/node_modules/@stdlib/utils/timeit/lib/vm_compile.js index de09d864a435..075bb4af3e58 100644 --- a/lib/node_modules/@stdlib/utils/timeit/lib/vm_compile.js +++ b/lib/node_modules/@stdlib/utils/timeit/lib/vm_compile.js @@ -38,21 +38,21 @@ function compile( filename, code ) { var script; var opts; - // Set the `vm` options: - opts = { - 'filename': filename, - 'lineOffset': 0, - 'displayErrors': true - }; - // Wrap the source code similar to `require`: code = wrap( code ); // Compile the source code: + opts = { + 'filename': filename, + 'lineOffset': 0 + }; script = new vm.Script( code, opts ); // Run the compiled code in the current V8 context: - return script.runInThisContext(); + opts = { + 'displayErrors': true + }; + return script.runInThisContext( opts ); } From d4110d3ad887b6875dc228edf28b776845b531ce Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 14 Mar 2019 22:27:15 -0700 Subject: [PATCH 019/142] Fix options --- .../_tools/test-cov/tape-istanbul/lib/compile.js | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/lib/node_modules/@stdlib/_tools/test-cov/tape-istanbul/lib/compile.js b/lib/node_modules/@stdlib/_tools/test-cov/tape-istanbul/lib/compile.js index d1fd77012fd7..52210493ce26 100644 --- a/lib/node_modules/@stdlib/_tools/test-cov/tape-istanbul/lib/compile.js +++ b/lib/node_modules/@stdlib/_tools/test-cov/tape-istanbul/lib/compile.js @@ -38,21 +38,21 @@ function compile( filename, code ) { var script; var opts; - // Set the `vm` options: - opts = { - 'filename': filename, - 'lineOffset': 0, - 'displayErrors': true - }; - // Wrap the source code similar to `require`: code = wrap( code ); // Compile the source code: + opts = { + 'filename': filename, + 'lineOffset': 0 + }; script = new vm.Script( code, opts ); // Run the compiled code in the current V8 context to generate a wrapped function: - return script.runInThisContext(); + opts = { + 'displayErrors': true + }; + return script.runInThisContext( opts ); } From cd20a3ee16a92ab297e9ec31a39e80e507bdb185 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 14 Mar 2019 22:40:47 -0700 Subject: [PATCH 020/142] Add initial REPL implementation --- .../@stdlib/repl/ctor/docs/clear.txt | 8 + .../@stdlib/repl/ctor/docs/example.txt | 28 + .../@stdlib/repl/ctor/docs/help.txt | 36 ++ .../@stdlib/repl/ctor/docs/load.txt | 14 + .../@stdlib/repl/ctor/docs/namespace.txt | 8 + .../@stdlib/repl/ctor/docs/quit.txt | 8 + .../@stdlib/repl/ctor/docs/record_start.txt | 23 + .../@stdlib/repl/ctor/docs/record_stop.txt | 25 + .../@stdlib/repl/ctor/docs/save.txt | 13 + .../@stdlib/repl/ctor/examples/index.js | 30 + .../@stdlib/repl/ctor/lib/create_context.js | 139 +++++ .../@stdlib/repl/ctor/lib/create_require.js | 116 ++++ .../@stdlib/repl/ctor/lib/defaults.js | 56 ++ .../@stdlib/repl/ctor/lib/help_text.js | 57 ++ .../@stdlib/repl/ctor/lib/main.js | 564 ++++++++++++++++++ .../@stdlib/repl/ctor/lib/validate.js | 116 ++++ .../@stdlib/repl/ctor/lib/welcome_text.js | 52 ++ 17 files changed, 1293 insertions(+) create mode 100644 lib/node_modules/@stdlib/repl/ctor/docs/clear.txt create mode 100644 lib/node_modules/@stdlib/repl/ctor/docs/example.txt create mode 100644 lib/node_modules/@stdlib/repl/ctor/docs/help.txt create mode 100644 lib/node_modules/@stdlib/repl/ctor/docs/load.txt create mode 100644 lib/node_modules/@stdlib/repl/ctor/docs/namespace.txt create mode 100644 lib/node_modules/@stdlib/repl/ctor/docs/quit.txt create mode 100644 lib/node_modules/@stdlib/repl/ctor/docs/record_start.txt create mode 100644 lib/node_modules/@stdlib/repl/ctor/docs/record_stop.txt create mode 100644 lib/node_modules/@stdlib/repl/ctor/docs/save.txt create mode 100644 lib/node_modules/@stdlib/repl/ctor/examples/index.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/create_context.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/create_require.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/defaults.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/help_text.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/main.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/validate.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/welcome_text.js diff --git a/lib/node_modules/@stdlib/repl/ctor/docs/clear.txt b/lib/node_modules/@stdlib/repl/ctor/docs/clear.txt new file mode 100644 index 000000000000..b3f3dfa8eba3 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/docs/clear.txt @@ -0,0 +1,8 @@ + +clear() + Clears the REPL context. + + Examples + -------- + > clear() + diff --git a/lib/node_modules/@stdlib/repl/ctor/docs/example.txt b/lib/node_modules/@stdlib/repl/ctor/docs/example.txt new file mode 100644 index 000000000000..2e4c2a37d4f8 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/docs/example.txt @@ -0,0 +1,28 @@ + +example( alias ) + Runs examples for a specified alias. + + Parameters + ---------- + alias: any + Alias (an object reference, literal, or a string). + + Examples + -------- + > example( {{alias:@stdlib/math/base/special/sin}} ) + > example( '{{alias:@stdlib/math/base/special/sin}}' ) + + +example( alias. ) + Runs examples for a specified property. + + Parameters + ---------- + alias.: any + Alias property (an object reference, literal, or a string). + + Examples + -------- + > example( {{alias:@stdlib/array/float64}}.from ) + > example( '{{alias:@stdlib/array/float64}}.from' ) + diff --git a/lib/node_modules/@stdlib/repl/ctor/docs/help.txt b/lib/node_modules/@stdlib/repl/ctor/docs/help.txt new file mode 100644 index 000000000000..1f7ec409e4be --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/docs/help.txt @@ -0,0 +1,36 @@ + +help() + Prints help text. + + Examples + -------- + > help() + + +help( alias ) + Prints help text for a specified alias. + + Parameters + ---------- + alias: any + Alias (an object reference, literal, or a string). + + Examples + -------- + > help( help ) + > help( 'help' ) + + +help( alias. ) + Prints help text for a specified property. + + Parameters + ---------- + alias.: any + Alias property (an object reference, literal, or a string). + + Examples + -------- + > help( {{alias:@stdlib/array/float64}}.from ) + > help( '{{alias:@stdlib/array/float64}}.from' ) + diff --git a/lib/node_modules/@stdlib/repl/ctor/docs/load.txt b/lib/node_modules/@stdlib/repl/ctor/docs/load.txt new file mode 100644 index 000000000000..2b9fad8f016c --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/docs/load.txt @@ -0,0 +1,14 @@ + +load( fpath ) + Loads and evaluates a JavaScript file, such as a REPL history file, line-by- + line. + + Parameters + ---------- + fpath: string + File path. + + Examples + -------- + > load( './path/to/file.js' ) + diff --git a/lib/node_modules/@stdlib/repl/ctor/docs/namespace.txt b/lib/node_modules/@stdlib/repl/ctor/docs/namespace.txt new file mode 100644 index 000000000000..21ab78077f34 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/docs/namespace.txt @@ -0,0 +1,8 @@ + +namespace() + Lists namespace contents. + + Examples + -------- + > namespace() + diff --git a/lib/node_modules/@stdlib/repl/ctor/docs/quit.txt b/lib/node_modules/@stdlib/repl/ctor/docs/quit.txt new file mode 100644 index 000000000000..34e1c08b5b03 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/docs/quit.txt @@ -0,0 +1,8 @@ + +quit() + Exits the REPL. + + Examples + -------- + > quit() + diff --git a/lib/node_modules/@stdlib/repl/ctor/docs/record_start.txt b/lib/node_modules/@stdlib/repl/ctor/docs/record_start.txt new file mode 100644 index 000000000000..bbb1d79bc48c --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/docs/record_start.txt @@ -0,0 +1,23 @@ + +recordStart( fpath ) + Starts saving commands to a specified file path. + + Parameters + ---------- + fpath: string + File path. + + Returns + ------- + id: number + Record identifier. + + Examples + -------- + > var id = recordStart( './path/to/file.js' ); + > 1 + 1 + 2 + > 'foo' + 'foo' + > recordStop( id ); + diff --git a/lib/node_modules/@stdlib/repl/ctor/docs/record_stop.txt b/lib/node_modules/@stdlib/repl/ctor/docs/record_stop.txt new file mode 100644 index 000000000000..f552e1eff5b9 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/docs/record_stop.txt @@ -0,0 +1,25 @@ + +recordStop( id ) + Stops saving commands to a file path associated with a specified record + identifier. + + Parameters + ---------- + id: number + Record identifier. + + Returns + ------- + bool: boolean + Boolean indicating whether the REPL successfully stopped saving + evaluated commands. + + Examples + -------- + > var id = recordStart( './path/to/file.js' ); + > 1 + 1 + 2 + > 'foo' + 'foo' + > recordStop( id ); + diff --git a/lib/node_modules/@stdlib/repl/ctor/docs/save.txt b/lib/node_modules/@stdlib/repl/ctor/docs/save.txt new file mode 100644 index 000000000000..28db238a0fe4 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/docs/save.txt @@ -0,0 +1,13 @@ + +save( fpath ) + Saves previous commands to a specified file path. + + Parameters + ---------- + fpath: string + File path. + + Examples + -------- + > save( './path/to/file.js' ) + diff --git a/lib/node_modules/@stdlib/repl/ctor/examples/index.js b/lib/node_modules/@stdlib/repl/ctor/examples/index.js new file mode 100644 index 000000000000..73b6dfa6c853 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var REPL = require( './../lib/main.js' ); + +function onExit() { + console.log( 'REPL closed.' ); +} + +// Create a new REPL: +var repl = new REPL(); + +repl.on( 'exit', onExit ); diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js new file mode 100644 index 000000000000..4aaa80531c2b --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -0,0 +1,139 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var Module = require( 'module' ); +var vm = require( 'vm' ); +var Console = require( 'console' ).Console; +var getGlobal = require( '@stdlib/utils/global' ); +var objectKeys = require( '@stdlib/utils/keys' ); +var setNonEnumerable = require( '@stdlib/utils/define-nonenumerable-property' ); +var defineProperty = require( '@stdlib/utils/define-property' ); +var createRequire = require( './create_require.js' ); + + +// VARIABLES // + +// TODO: remove once we have stdlib pkg equivalents +var GLOBALS = { + 'Array': Array, + 'Boolean': Boolean, + 'Date': Date, + 'Function': Function, + 'Object': Object, + 'parseFloat': parseFloat, + 'parseInt': parseInt, + 'RegExp': RegExp, + 'String': String, + + // TODO: BigInt, DataView, Map, Set, Promise, Reflect(?), WeakMap, WeakSet, WebAssembly + + 'Error': Error, + 'EvalError': EvalError, + 'RangeError': RangeError, + 'ReferenceError': ReferenceError, + 'SyntaxError': SyntaxError, + 'TypeError': TypeError, + 'URIError': URIError, + + 'clearImmediate': clearImmediate, + 'clearInterval': clearInterval, + 'clearTimeout': clearTimeout, + 'setImmediate': setImmediate, + 'setInterval': setInterval, + 'setTimeout': setTimeout +}; + +// Cache references to module methods (WARNING: we use private methods exposed on the `Module` object; thus, breakage is possible!): +var resolveLookupPaths = Module._resolveLookupPaths; // eslint-disable-line no-underscore-dangle + + +// MAIN // + +/** +* Creates a REPL context. +* +* @private +* @param {Options} options - context options +* @param {boolean} options.sandbox - boolean indicating whether to create a sandboxed context +* @param {WritableStream} options.output - output stream +* @returns {Object} REPL context +*/ +function createContext( options ) { + var Global; + var keys; + var ctx; + var i; + + Global = getGlobal(); + if ( options.sandbox ) { + // Create a sandboxed context: + ctx = vm.createContext(); + + // Assign globals from the current global context to the sandboxed context (note: shallow copy!)... + keys = objectKeys( GLOBALS ); + for ( i = 0; i < keys.length; i++ ) { + setNonEnumerable( ctx, keys[ i ], GLOBALS[ keys[ i ] ] ); + } + + // Create a circular reference as in Node: + ctx.global = ctx; + + // Create a new console interface: + setNonEnumerable( ctx, 'console', new Console( options.output ) ); + + // Create a new `module` object: + setNonEnumerable( ctx, 'module', new Module( '' ) ); + + // Create a new `require` function: + setNonEnumerable( ctx, 'require', createRequire( ctx.module ) ); + } else { + ctx = Global; + + // Create a new `module` object: + defineProperty( ctx, 'module', { + 'configurable': true, + 'writable': false, + 'enumerable': false, + 'value': new Module( '' ) + }); + + // Create a new `require` function: + defineProperty( ctx, 'require', { + 'configurable': true, + 'writable': false, + 'enumerable': false, + 'value': createRequire( ctx.module ) + }); + } + ctx.module.paths = resolveLookupPaths( '', module, true ) || []; + + // TODO: lazy load project APIs (configurable, enumerable accessors which overwrite themselves to become read-only properties; see https://github.com/nodejs/node/blob/0c1e93b9efadfc9fae74907a631908477c7d085e/lib/internal/modules/cjs/helpers.js#L102) + + // TODO: add REPL-specific APIs, such as `help`, etc. + + return ctx; +} + + +// EXPORTS // + +module.exports = createContext; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_require.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_require.js new file mode 100644 index 000000000000..39b85da0e607 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_require.js @@ -0,0 +1,116 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/* +* WARNING: this is based an internal file within Node.js. The implementation uses private methods exposed on the `Module` object. Given that they are private, breakage is possible. +* +* [1]: https://github.com/nodejs/node/blob/0c1e93b9efadfc9fae74907a631908477c7d085e/lib/internal/modules/cjs/helpers.js#L10 +*/ + +// MODULES // + +var Module = require( 'module' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; + + +// VARIABLES // + +/* eslint-disable no-underscore-dangle */ +var resolveFilename = Module._resolveFilename; +var resolveLookupPaths = Module._resolveLookupPaths; +var extensions = Module._extensions; +var cache = Module._cache; +var main = process.mainModule; + +/* eslint-enable no-underscore-dangle */ + + +// MAIN // + +/** +* Returns a `require` function. +* +* @private +* @param {Module} module - module used as the context for `require` +* @returns {Function} require function +*/ +function createRequire( module ) { + /** + * Attempts to load a module. + * + * @private + * @param {string} path - module id + * @returns {*} module + */ + function require( path ) { + return module.require( path ); + } + + /** + * Attempts to resolve a module. + * + * @private + * @param {string} name - module + * @param {Object} [options] - options + * @throws {TypeError} first argument must be a string + * @returns {string} module filepath + */ + function resolve( name, options ) { + if ( !isString( name ) ) { + throw new TypeError( 'invalid argument. First argument must be a string. Value: `' + name + '`.' ); + } + return resolveFilename( name, module, false, options ); + } + + /** + * Attempts to resolve look-up paths. + * + * @private + * @param {string} name - module + * @throws {TypeError} must provide a string + * @returns {(StringArray|null)} resolved paths + */ + function paths( name ) { + if ( !isString( name ) ) { + throw new TypeError( 'invalid argument. Must provide a string. Value: `' + name + '`.' ); + } + return resolveLookupPaths( name, module, true ); + } + + // Script entry point when Node.js process launched: + require.main = main; + + // Attach method to resolve a module: + resolve.paths = paths; + require.resolve = resolve; + + // Support for extra extension types: + require.extensions = extensions; + + // Use the existing module cache: + require.cache = cache; + + return require; +} + + +// EXPORTS // + +module.exports = createRequire; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/defaults.js b/lib/node_modules/@stdlib/repl/ctor/lib/defaults.js new file mode 100644 index 000000000000..d1e6ed3ace66 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/defaults.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stdin = require( '@stdlib/streams/node/stdin' ); +var stdout = require( '@stdlib/streams/node/stdout' ); +var WELCOME = require( './welcome_text.js' ); + + +// MAIN // + +/** +* Returns default options. +* +* @private +* @returns {Object} default options +* +* @example +* var opts = defaults(); +* // returns {...} +*/ +function defaults() { + return { + 'input': stdin, + 'output': stdout, + 'prompt': '> ', + 'isTTY': void 0, + 'sandbox': true, + 'welcome': WELCOME, + 'save': '', + 'load': '' + }; +} + + +// EXPORTS // + +module.exports = defaults; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js b/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js new file mode 100644 index 000000000000..ac3fec7903f9 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +var MSG = [ + '', + ' help() Prints help text.', + ' help( alias ) Prints help text for a specified alias.', + ' help( alias. ) Prints help text for a specified property.', + '', + ' example( alias ) Runs examples for a specified alias.', + ' example( alias. ) Runs examples for a specified property.', + '', + ' namespace() Lists namespace contents.', + ' alias2pkg( alias ) Converts an alias to a stdlib package name.', + ' pkg2alias( pkg ) Converts a stdlib package name to an alias.', + '', + ' load( fpath ) Loads and evaluates a JavaScript file line-by-line.', + ' save( fpath ) Saves previous commands to a specified file.', + ' recordStart( fpath ) Start saving commands to a specified file.', + ' recordStop( id ) Stop saving commands.', + '', + ' clear() Clears the REPL context.', + ' quit() Exits the REPL.', + '', + ' citation() Prints how to cite stdlib in publications.', + ' license() Prints license information.', + ' copyright() Prints copyright information.', + ' contributors() Lists contributors.', + ' credits() Prints credits.', + ' donate() Prints donation information.', + '', + '' +].join( '\n' ); + + +// EXPORTS // + +module.exports = MSG; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js new file mode 100644 index 000000000000..941056462e54 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -0,0 +1,564 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable no-restricted-syntax, no-invalid-this */ + +'use strict'; + +// MODULES // + +var EventEmitter = require( 'events' ).EventEmitter; +var readline = require( 'readline' ).createInterface; +var resolve = require( 'path' ).resolve; +var vm = require( 'vm' ); +var inspect = require( 'util' ).inspect; +var logger = require( 'debug' ); +var inherit = require( '@stdlib/utils/inherit' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var setNonEnumerable = require( '@stdlib/utils/define-nonenumerable-property' ); +var setNonEnumerableReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var setNonEnumerableReadOnlyAccessor = require( '@stdlib/utils/define-nonenumerable-read-only-accessor' ); // eslint-disable-line id-length +var trim = require( '@stdlib/string/trim' ); +var cwd = require( '@stdlib/process/cwd' ); +var readFileSync = require( '@stdlib/fs/read-file' ).sync; +var RE_EOL = require( '@stdlib/regexp/eol' ); +var fifo = require( '@stdlib/utils/fifo' ); +var validate = require( './validate.js' ); +var defaults = require( './defaults.js' ); +var createContext = require( './create_context.js' ); + + +// VARIABLES // + +var debug = logger( 'repl' ); +var SEMICOLON = 59; // character code +var RE_OPENING_BRACE = /^\s*\{/; +var RE_CLOSING_BRACE = /\}\s*$/; +var RE_WHITESPACE = /^\s*$/; + +/* +* In certain JavaScript engines (e.g., V8, SpiderMonkey), the global `RegExp` object has ([non-standard][1]) static, read-only properties (`$1`, `$2`, ..., `$9`) with cached substring matches. In order to preserve these matches between command evaluations, we need to capture and subsequently restore them prior to evaluation. +* +* [1]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/RegExp/n +*/ +var SEP_REGEXP_MATCHES = '\u0000\u0000\u0000'; +var RE_REGEXP_MATCHES = new RegExp( [ '^', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)$' ].join( SEP_REGEXP_MATCHES ) ); + + +// FUNCTIONS // + +/** +* Displays a command prompt. +* +* @private +* @param {ReadlineInterface} rli - readline interface +* @param {Array} cmd - command buffer +* @param {string} prompt - default prompt +* @param {boolean} [preserveCursor=false] - boolean indicating whether to preserve the cursor position +*/ +function displayPrompt( rli, cmd, prompt, preserveCursor ) { + var out; + if ( cmd.length ) { + // TODO: determine indentation level (use spaces) + out = ''; + } else { + out = prompt; + } + rli.setPrompt( out ); + rli.prompt( preserveCursor ); +} + +/** +* Updates the cache of saved regular expression substring matches. +* +* @private +* @param {StringArray} cache - list of previously saved substring matches +* @returns {StringArray} cache +*/ +function updateRegExpCache( cache ) { + var i; + for ( i = 1; i < cache.length; i++ ) { + cache[ i ] = RegExp[ '$'+i ]; + } + return cache; +} + +/** +* Restores the (non-standard) properties on the `RegExp` expression object to the cached matches. +* +* @private +* @param {StringArray} cache - list of previously saved substring matches +*/ +function restoreRegExpMatches( cache ) { + RE_REGEXP_MATCHES.test( cache.join( SEP_REGEXP_MATCHES ) ); +} + + +// MAIN // + +/** +* REPL constructor. +* +* @param {Options} options - constructor options +* @param {string} [options.prompt='> '] - input prompt +* @param {ReadableStream} [options.input=process.stdin] - input stream +* @param {WritableStream} [options.output=process.stdout] - output stream +* @param {boolean} [options.sandbox=true] - boolean indicating whether to run a REPL in a sandboxed context +* @param {boolean} [options.isTTY] - boolean indicating whether the input and output streams should be treated like a TTY (terminal) and whether the REPL should ANSI/VT100 escape codes when writing to the output stream +* @param {string} [options.welcome] - welcome message +* @param {string} [options.load] - file path specifying a JavaScript file to load and evaluate line-by-line (e.g., a previous REPL history file) +* @param {string} [options.save] - file path specifying where to save REPL history +* @throws {Error} must provide valid options +* @returns {REPL} REPL instance +* +* @example +* // TODO +*/ +function REPL( options ) { + var SAVED_REGEXP_MATCHES; + var istream; + var ostream; + var context; + var history; + var queue; + var busy; + var opts; + var self; + var cmd; + var ans; + var rli; + var err; + + if ( !( this instanceof REPL ) ) { + if ( arguments.length ) { + return new REPL( options ); + } + return new REPL(); + } + self = this; + + opts = defaults(); + if ( arguments.length ) { + err = validate( opts, options ); + if ( err ) { + throw err; + } + } + opts.isTTY = ( opts.isTTY === void 0 ) ? opts.output.isTTY : opts.isTTY; + + debug( 'Options: %s', JSON.stringify({ + 'input': '', + 'output': '', + 'sandbox': opts.sandbox, + 'isTTY': opts.isTTY, + 'prompt': opts.prompt, + 'welcome': opts.welcome, + 'load': opts.load, + 'save': opts.save + })); + + // Call the parent constructor: + EventEmitter.call( this ); + + // Cache references to the input and output streams: + istream = opts.input; + ostream = opts.output; + + // Initialize an array for storing the command history: + history = []; + + // Initialize a "buffer" for storing the current command: + cmd = []; + + // Initialize a flag indicating whether the REPL is currently busy with asynchronous processing: + busy = false; + + // Initialize an array for saving regular expression matches between command evaluations: + SAVED_REGEXP_MATCHES = [ '', '', '', '', '', '', '', '', '', '' ]; + + // Create an internal readline interface: + debug( 'Creating readline interface...' ); + rli = readline({ + 'input': istream, + 'output': ostream, + 'terminal': opts.isTTY, + 'prompt': opts.prompt + }); + rli.on( 'close', onClose ); + rli.on( 'line', onLine ); + + // Cache a reference to the readline interface: + setNonEnumerableReadOnly( this, '_rli', rli ); + + // Create an internal flag indicating whether the REPL has been closed: + setNonEnumerable( this, '_closed', false ); + + // Initialize a command queue: + queue = fifo(); + setNonEnumerableReadOnly( this, '_queue', queue ); + + // Add a public method for clearing a REPL: + setNonEnumerableReadOnly( this, 'clear', clear ); + + // Create a REPL execution context: + createNewContext(); + + // Write a welcome message: + ostream.write( opts.welcome ); + + // TODO: check whether to synchronously initialize a REPL history file + + // Check whether to load and execute a JavaScript file (e.g., prior REPL history) upon startup... + if ( opts.load ) { + this.load( opts.load ); + } else { + displayPrompt( rli, cmd, opts.prompt, false ); + } + return this; + + /** + * Callback invoked upon receiving a readline interface "line" event. + * + * @private + * @param {string} line - line data + * @returns {void} + */ + function onLine( line ) { + var isWrapped; + var script; + var sopts; + var code; + + debug( 'Line: %s', line ); + + // Removing leading and trailing whitespace: + line = trim( line ); + + // TODO: check if the line is valid JavaScript syntax; if yes, then proceed; otherwise, buffer the command in `cmd` buffer until ready to execute (e.g., when providing multi-line input) + + sopts = { + 'filename': '', + 'lineOffset': 0 + }; + code = { + 'raw': line + }; + + // Check for commands like object literals (e.g., `{'a':1}`), which we want to be evaluated as expressions, rather than blocks... + if ( RE_OPENING_BRACE.test( line ) && RE_CLOSING_BRACE.test( line ) ) { + // FIXME: we need to actually parse into an AST here and check if the last "expression" begins and ends with braces (e.g., `1+1; {'a':1}`); if so, we need to wrap the last expression in parentheses + // FIXME: the above also fails to account for `{'a':1};`, which ends in a semicolon and not a brace + // FIXME: the above also fails to account for expressions such as variable assignments (e.g., `var v = [1,2,3]`), where we may want to see the assigned value + line = '(' + line + ')\n'; + isWrapped = true; + } + // Attempt to compile the command... + while ( true ) { + try { + if ( RE_WHITESPACE.test( line ) ) { + script = new vm.Script( line, sopts ); + code.silent = true; + } else { + // Note: `void 0` ensures that the compiled script does not return the string `'use strict'` when provided commands (statements/declarations) which do not return a value (e.g., `{}`): + script = new vm.Script( '\'use strict\'; void 0;\n'+line, sopts ); + code.silent = line.charCodeAt( line.length-1 ) === SEMICOLON; // eslint-disable-line max-len + } + code.compiled = script; + } catch ( error ) { + // If we previously wrapped the command, unwrap and try again... + if ( isWrapped ) { + isWrapped = false; + line = code.raw; + continue; + } + // TODO: check if error is recoverable? And if so, update the command buffer; otherwise, write error message to console and display prompt. + debug( 'Error: %s', error.message ); + ostream.write( 'Error: '+error.message+'\n' ); + displayPrompt( rli, cmd, opts.prompt, false ); + return; + } + break; + } + // Add the command to the command queue: + queue.push( code ); + + // Request to run the command: + drain(); + } + + /** + * Callback invoked upon a readline interface "close" event. + * + * @private + */ + function onClose() { + debug( 'Readline interface closed.' ); + debug( 'Exiting the REPL...' ); + self.emit( 'exit' ); + } + + /** + * Creates a REPL execution context. + * + * @private + * @returns {Object} REPL context + */ + function createNewContext() { + debug( 'Creating REPL execution context...' ); + + // Create a new context: + context = createContext({ + 'sandbox': opts.sandbox, + 'output': ostream + }); + + // TODO: add commands + setNonEnumerableReadOnly( context, 'clear', clear ); + setNonEnumerableReadOnly( context, 'load', load ); + setNonEnumerableReadOnly( context, 'quit', quit ); + + // Add an accessor for retrieving the result of the last successfully executed command: + setNonEnumerableReadOnlyAccessor( context, 'ans', getLastAnswer ); + + return context; + } + + /** + * Returns the result of the last successfully executed command. + * + * @private + * @returns {*} result + */ + function getLastAnswer() { + return ans; + } + + /** + * Drains the command queue. + * + * @private + * @returns {void} + */ + function drain() { + var sopts; + var code; + var res; + + if ( queue.length === 0 ) { + debug( 'Command queue is empty.' ); + busy = false; + if ( !self._closed ) { // eslint-disable-line no-underscore-dangle + displayPrompt( rli, cmd, opts.prompt, false ); + } + return; + } + if ( busy ) { + debug( 'Waiting on an asynchronous command to finish.' ); + return; + } + debug( 'Evaluating next command...' ); + + // Remove a command from the queue: + code = queue.pop(); + debug( 'Command: %s', code.raw ); + + // TODO: check whether command begins with `await` or `for await` (the latter would allow for updating the last line of output; e.g., an ASCII chart!); if so, then async processing and set `busy` to true; otherwise, assume sync processing + + // Set the (non-standard) properties on the `RegExp` expression object to the cached matches: + restoreRegExpMatches( SAVED_REGEXP_MATCHES ); + + // TODO: evaluate and determine whether to print result + sopts = { + 'displayErrors': false, + 'breakOnSigint': true // Note: applies only for Node.js versions >=6.3.0 + }; + try { + if ( opts.sandbox ) { + res = code.compiled.runInContext( context, sopts ); + } else { + res = code.compiled.runInThisContext( sopts ); + } + updateRegExpCache( SAVED_REGEXP_MATCHES ); + } catch ( error ) { + updateRegExpCache( SAVED_REGEXP_MATCHES ); + + // TODO: handle SIGINT (see https://github.com/nodejs/node/blob/b21e7c7bcf23a2715951e4cd96180e4dbf1dcd4d/lib/repl.js#L581) + + // TODO: check if error is recoverable + debug( 'Error: %s', error.message ); + ostream.write( 'Error: '+error.message+'\n' ); + displayPrompt( rli, cmd, opts.prompt, false ); + return; + } + if ( code.silent === false && res !== void 0 ) { + ostream.write( inspect( res )+'\n' ); // TODO: pretty printing (can defer to `util.inspect` for now, but will invariably want more control over this later, possibly including default configuration, etc, either at startup, during runtime, or according to an external configuration file) + } + // Cache the result: + ans = res; + + // TODO: if successful, save the command in the history buffer and, if necessary, write to a history file + + // TODO: replace with polyfill + process.nextTick( drain ); + } + + /** + * Clears the local context. + * + * @private + */ + function clear() { + debug( 'Clearing the local REPL context...' ); + + // Clear the command queue: + queue.clear(); + + // Clear any command which has been buffered but not yet executed: + cmd.length = 0; + + // Clear the command history: + history.length = 0; + + // When sandboxed, create a new execution context... + if ( opts.sandbox ) { + context = createNewContext(); + self.emit( 'reset', context ); + } + // TODO: clear the window of any previous commands and output + + // Display the command prompt: + displayPrompt( rli, cmd, opts.prompt, false ); + } + + /** + * Loads and evaluates a JavaScript file line-by-line. + * + * @private + * @param {string} fpath - file path + * @returns {void} + */ + function load( fpath ) { + var err; + if ( !isString( fpath ) ) { + err = new TypeError( 'invalid argument. Must provide a string. Value: `'+fpath+'`.' ); + debug( 'Error: %s', err.message ); + ostream.write( 'Error: '+err.message+'\n' ); + return; + } + debug( 'Loading a file...' ); + self.load( fpath ); + } + + /** + * Quits a REPL. + * + * @private + */ + function quit() { + debug( 'Quitting the REPL...' ); + self.close(); + } +} + +/* +* Inherit from the `EventEmitter` prototype. +*/ +inherit( REPL, EventEmitter ); + +/** +* Loads and evaluates a JavaScript file line-by-line. +* +* ## Notes +* +* - The method **synchronously** reads provided files in order to preserve command order. +* +* @name load +* @memberof REPL.prototype +* @type {Function} +* @param {string} fpath - file path +* @throws {TypeError} must provide a string +* @returns {REPL} REPL instance +*/ +setNonEnumerableReadOnly( REPL.prototype, 'load', function load( fpath ) { + var file; + var i; + if ( !isString( fpath ) ) { + throw new TypeError( 'invalid argument. Must provide a string. Value: `' + fpath + '`.' ); + } + // Resolve the provided path to an absolute file path: + fpath = resolve( cwd(), fpath ); + debug( 'Loading filepath: %s', fpath ); + + // Attempt to synchronously read the file: + file = readFileSync( fpath, 'utf8' ); + if ( file instanceof Error ) { + debug( 'Error: %s', file.message ); + this._ostream.write( 'Error: '+file.message+'\n' ); + return this; + } + // Split the file content into individual lines: + file = file.split( RE_EOL ); + + // Forward each line to the REPL readline interface in order to mimic user input... + for ( i = 0; i < file.length; i++ ) { + this._rli.write( file[ i ] ); + } + return this; +}); + +/** +* Closes a REPL. +* +* @name close +* @memberof REPL.prototype +* @type {Function} +* @returns {REPL} REPL instance +*/ +setNonEnumerableReadOnly( REPL.prototype, 'close', function close() { + var self; + if ( this._closed ) { + debug( 'Attempted to close an already closed REPL.' ); + return this; + } + self = this; + this._closed = true; + + // Clear the command queue: + this._queue.clear(); + + // TODO: ensure REPL history is saved (flushed) to file before closing the REPL (see https://github.com/nodejs/node/blob/b21e7c7bcf23a2715951e4cd96180e4dbf1dcd4d/lib/repl.js#L805) + + process.nextTick( onTick ); // TODO: replace with polyfill + + return this; + + /** + * Callback invoked upon the next tick of the event loop. + * + * @private + */ + function onTick() { + debug( 'Closing the readline interface...' ); + self._rli.close(); // eslint-disable-line no-underscore-dangle + } +}); + + +// EXPORTS // + +module.exports = REPL; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/validate.js b/lib/node_modules/@stdlib/repl/ctor/lib/validate.js new file mode 100644 index 000000000000..d5ee4b9a85d5 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/validate.js @@ -0,0 +1,116 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isPlainObject = require( '@stdlib/assert/is-plain-object' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var isReadableStreamLike = require( '@stdlib/assert/is-node-readable-stream-like' ); +var isWritableStreamLike = require( '@stdlib/assert/is-node-writable-stream-like' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; + + +// MAIN // + +/** +* Validates function options. +* +* @private +* @param {Object} opts - destination object +* @param {Options} options - function options +* @param {string} [options.prompt] - input prompt +* @param {ReadableStream} [options.input=] - input stream +* @param {WritableStream} [options.output] - output stream +* @param {boolean} [options.sandbox] - boolean indicating whether to run a REPL in a sandboxed context +* @param {boolean} [options.isTTY] - boolean indicating whether the input and output streams should be treated like a TTY (terminal) and whether the REPL should ANSI/VT100 escape codes when writing to the output stream +* @param {string} [options.welcome] - welcome message +* @param {string} [options.load] - file path specifying a JavaScript file to load and evaluate line-by-line (e.g., a previous REPL history file) +* @param {string} [options.save] - file path specifying where to save REPL history +* @throws {Error} must provide valid options +* @returns {(Error|null)} error or null +* +* @example +* var options = {}; +* var opts = {}; +* var err = validate( opts, options ); +* if ( err ) { +* throw err; +* } +*/ +function validate( opts, options ) { + if ( !isPlainObject( options ) ) { + return new TypeError( 'invalid argument. Options argument must be an object. Value: `' + options + '`.' ); + } + if ( hasOwnProp( options, 'input' ) ) { + opts.input = options.input; + if ( !isReadableStreamLike( options.input ) ) { + return new TypeError( 'invalid option. `input` option must be a readable stream. Option: `' + options.input + '`.' ); + } + } + if ( hasOwnProp( options, 'output' ) ) { + opts.output = options.output; + if ( !isWritableStreamLike( options.output ) ) { + return new TypeError( 'invalid option. `output` option must be a writable stream. Option: `' + options.output + '`.' ); + } + } + if ( hasOwnProp( options, 'prompt' ) ) { + opts.prompt = options.prompt; + if ( !isString( options.prompt ) ) { + return new TypeError( 'invalid option. `prompt` option must be a string. Option: `' + options.prompt + '`.' ); + } + } + if ( hasOwnProp( options, 'welcome' ) ) { + opts.welcome = options.welcome; + if ( !isString( options.welcome ) ) { + return new TypeError( 'invalid option. `welcome` option must be a string. Option: `' + options.welcome + '`.' ); + } + } + if ( hasOwnProp( options, 'save' ) ) { + opts.save = options.save; + if ( !isString( options.save ) ) { + return new TypeError( 'invalid option. `save` option must be a string. Option: `' + options.save + '`.' ); + } + } + if ( hasOwnProp( options, 'load' ) ) { + opts.load = options.load; + if ( !isString( options.load ) ) { + return new TypeError( 'invalid option. `load` option must be a string. Option: `' + options.load + '`.' ); + } + } + if ( hasOwnProp( options, 'isTTY' ) ) { + opts.isTTY = options.isTTY; + if ( !isBoolean( options.isTTY ) ) { + return new TypeError( 'invalid option. `isTTY` option must be a boolean. Option: `' + options.isTTY + '`.' ); + } + } + if ( hasOwnProp( options, 'sandbox' ) ) { + opts.sandbox = options.sandbox; + if ( !isBoolean( options.sandbox ) ) { + return new TypeError( 'invalid option. `sandbox` option must be a boolean. Option: `' + options.sandbox + '`.' ); + } + } + return null; +} + + +// EXPORTS // + +module.exports = validate; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/welcome_text.js b/lib/node_modules/@stdlib/repl/ctor/lib/welcome_text.js new file mode 100644 index 000000000000..7ef8c295678c --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/welcome_text.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +var MSG = [ + '', + 'A better REPL for JavaScript and Node.js.', + + // TODO: include platform, copyright, version (see Julia, R, and Python for inspiration) + '', + ' help() Prints help text.', + ' help( alias ) Prints help text for a specified alias.', + ' help( alias. ) Prints help text for a specified property.', + '', + ' example( alias ) Runs examples for a specified alias.', + ' example( alias. ) Runs examples for a specified property.', + '', + ' clear() Clears the list of previous commands.', + ' quit() Exits the REPL.', + '', + ' license() Prints license information.', + ' copyright() Prints copyright information.', + '', + 'For more info about stdlib, see the source repository:', + '', + ' https://github.com/stdlib-js/stdlib', + '', + '' +].join( '\n' ); + + +// EXPORTS // + +module.exports = MSG; From de907d510219f541f79d362825ec9e9b93fdeede Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 00:35:14 -0700 Subject: [PATCH 021/142] Clear entire screen and scrollback history --- .../@stdlib/repl/ctor/lib/create_context.js | 4 +- .../@stdlib/repl/ctor/lib/main.js | 39 +++++++++++++++---- .../@stdlib/repl/ctor/lib/validate.js | 2 +- 3 files changed, 34 insertions(+), 11 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 4aaa80531c2b..107c8de050ed 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -126,9 +126,7 @@ function createContext( options ) { } ctx.module.paths = resolveLookupPaths( '', module, true ) || []; - // TODO: lazy load project APIs (configurable, enumerable accessors which overwrite themselves to become read-only properties; see https://github.com/nodejs/node/blob/0c1e93b9efadfc9fae74907a631908477c7d085e/lib/internal/modules/cjs/helpers.js#L102) - - // TODO: add REPL-specific APIs, such as `help`, etc. + // TODO: lazy load project APIs (configurable, enumerable(?) accessors which overwrite themselves to become read-only properties; see https://github.com/nodejs/node/blob/0c1e93b9efadfc9fae74907a631908477c7d085e/lib/internal/modules/cjs/helpers.js#L102) return ctx; } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index 941056462e54..ec74cb8a8e0d 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -23,7 +23,7 @@ // MODULES // var EventEmitter = require( 'events' ).EventEmitter; -var readline = require( 'readline' ).createInterface; +var readline = require( 'readline' ); var resolve = require( 'path' ).resolve; var vm = require( 'vm' ); var inspect = require( 'util' ).inspect; @@ -119,7 +119,7 @@ function restoreRegExpMatches( cache ) { * @param {ReadableStream} [options.input=process.stdin] - input stream * @param {WritableStream} [options.output=process.stdout] - output stream * @param {boolean} [options.sandbox=true] - boolean indicating whether to run a REPL in a sandboxed context -* @param {boolean} [options.isTTY] - boolean indicating whether the input and output streams should be treated like a TTY (terminal) and whether the REPL should ANSI/VT100 escape codes when writing to the output stream +* @param {boolean} [options.isTTY] - boolean indicating whether the input and output streams should be treated like a TTY (terminal) and whether the REPL should use ANSI/VT100 escape codes when writing to the output stream * @param {string} [options.welcome] - welcome message * @param {string} [options.load] - file path specifying a JavaScript file to load and evaluate line-by-line (e.g., a previous REPL history file) * @param {string} [options.save] - file path specifying where to save REPL history @@ -193,7 +193,7 @@ function REPL( options ) { // Create an internal readline interface: debug( 'Creating readline interface...' ); - rli = readline({ + rli = readline.createInterface({ 'input': istream, 'output': ostream, 'terminal': opts.isTTY, @@ -327,11 +327,24 @@ function REPL( options ) { 'output': ostream }); - // TODO: add commands + // Add commands requiring privileged access to internal instance variables: setNonEnumerableReadOnly( context, 'clear', clear ); setNonEnumerableReadOnly( context, 'load', load ); setNonEnumerableReadOnly( context, 'quit', quit ); + // TODO: add `help` command + // TODO: add `example` command + // TODO: add `namespace` command + // TODO: add `save` command + // TODO: add `recordStart` command + // TODO: add `recordStop` command + // TODO: add `citation` command + // TODO: add `license` command + // TODO: add `copyright` command + // TODO: add `contributors` command + // TODO: add `credits` command + // TODO: add `donate` command + // Add an accessor for retrieving the result of the last successfully executed command: setNonEnumerableReadOnlyAccessor( context, 'ans', getLastAnswer ); @@ -368,7 +381,7 @@ function REPL( options ) { return; } if ( busy ) { - debug( 'Waiting on an asynchronous command to finish.' ); + debug( 'Waiting on an asynchronous command to finish...' ); return; } debug( 'Evaluating next command...' ); @@ -439,8 +452,20 @@ function REPL( options ) { context = createNewContext(); self.emit( 'reset', context ); } - // TODO: clear the window of any previous commands and output - + // Clear an output TTY stream of any previous commands and output: + if ( opts.isTTY ) { + /* + * Clear the entire screen and scrollback history using [ANSI escape sequences][1]. + * + * - `\u001b`: ESC, the escape character + * - `[H`: move cursor to upper left corner + * - `[2J`: clear the entire screen + * - `[3J`: clear the entire screen and delete all lines in the scrollback buffer + * + * [1]: https://en.wikipedia.org/wiki/ANSI_escape_code + */ + ostream.write( '\u001b[2J\u001b[H\u001b[2J\u001b[3J' ); + } // Display the command prompt: displayPrompt( rli, cmd, opts.prompt, false ); } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/validate.js b/lib/node_modules/@stdlib/repl/ctor/lib/validate.js index d5ee4b9a85d5..e51ed295288a 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/validate.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/validate.js @@ -40,7 +40,7 @@ var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; * @param {ReadableStream} [options.input=] - input stream * @param {WritableStream} [options.output] - output stream * @param {boolean} [options.sandbox] - boolean indicating whether to run a REPL in a sandboxed context -* @param {boolean} [options.isTTY] - boolean indicating whether the input and output streams should be treated like a TTY (terminal) and whether the REPL should ANSI/VT100 escape codes when writing to the output stream +* @param {boolean} [options.isTTY] - boolean indicating whether the input and output streams should be treated like a TTY (terminal) and whether the REPL should use ANSI/VT100 escape codes when writing to the output stream * @param {string} [options.welcome] - welcome message * @param {string} [options.load] - file path specifying a JavaScript file to load and evaluate line-by-line (e.g., a previous REPL history file) * @param {string} [options.save] - file path specifying where to save REPL history From c5c1c6d1214f43fb6c1c11db6c5a9284d1f9a411 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 01:15:38 -0700 Subject: [PATCH 022/142] Refactor into functions which operate on a REPL instance --- .../@stdlib/repl/ctor/lib/main.js | 626 +++++++++--------- 1 file changed, 325 insertions(+), 301 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index ec74cb8a8e0d..836ac358f9ca 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -16,7 +16,7 @@ * limitations under the License. */ -/* eslint-disable no-restricted-syntax, no-invalid-this */ +/* eslint-disable no-restricted-syntax, no-invalid-this, no-underscore-dangle */ 'use strict'; @@ -66,21 +66,298 @@ var RE_REGEXP_MATCHES = new RegExp( [ '^', '(.*)', '(.*)', '(.*)', '(.*)', '(.*) * Displays a command prompt. * * @private -* @param {ReadlineInterface} rli - readline interface -* @param {Array} cmd - command buffer -* @param {string} prompt - default prompt +* @param {REPL} repl - REPL instance * @param {boolean} [preserveCursor=false] - boolean indicating whether to preserve the cursor position */ -function displayPrompt( rli, cmd, prompt, preserveCursor ) { - var out; - if ( cmd.length ) { +function displayPrompt( repl, preserveCursor ) { + var prompt; + if ( repl._cmd.length ) { // TODO: determine indentation level (use spaces) - out = ''; + prompt = ''; } else { - out = prompt; + prompt = repl._prompt; + } + repl._rli.setPrompt( prompt ); + repl._rli.prompt( preserveCursor ); +} + +/** +* Processes input line data. +* +* @private +* @param {REPL} repl - REPL instance +* @param {string} line - line data +* @returns {void} +*/ +function processLine( repl, line ) { + var isWrapped; + var script; + var opts; + var code; + + debug( 'Line: %s', line ); + + // Removing leading and trailing whitespace: + line = trim( line ); + + // TODO: check if the line is valid JavaScript syntax; if yes, then proceed; otherwise, buffer the command in `cmd` buffer until ready to execute (e.g., when providing multi-line input) + + opts = { + 'filename': '', + 'lineOffset': 0 + }; + code = { + 'raw': line + }; + + // Check for commands like object literals (e.g., `{'a':1}`), which we want to be evaluated as expressions, rather than blocks... + if ( RE_OPENING_BRACE.test( line ) && RE_CLOSING_BRACE.test( line ) ) { + // FIXME: we need to actually parse into an AST here and check if the last "expression" begins and ends with braces (e.g., `1+1; {'a':1}`); if so, we need to wrap the last expression in parentheses + // FIXME: the above also fails to account for `{'a':1};`, which ends in a semicolon and not a brace + // FIXME: the above also fails to account for expressions such as variable assignments (e.g., `var v = [1,2,3]`), where we may want to see the assigned value + line = '(' + line + ')\n'; + isWrapped = true; + } + // Attempt to compile the command... + while ( true ) { + try { + if ( RE_WHITESPACE.test( line ) ) { + script = new vm.Script( line, opts ); + code.silent = true; + } else { + // Note: `void 0` ensures that the compiled script does not return the string `'use strict'` when provided commands (statements/declarations) which do not return a value (e.g., `{}`): + script = new vm.Script( '\'use strict\'; void 0;\n'+line, opts ); + code.silent = line.charCodeAt( line.length-1 ) === SEMICOLON; // eslint-disable-line max-len + } + code.compiled = script; + } catch ( error ) { + // If we previously wrapped the command, unwrap and try again... + if ( isWrapped ) { + isWrapped = false; + line = code.raw; + continue; + } + // TODO: check if error is recoverable? And if so, update the command buffer; otherwise, write error message to console and display prompt. + debug( 'Error: %s', error.message ); + repl._ostream.write( 'Error: '+error.message+'\n' ); + displayPrompt( repl, false ); + return; + } + break; + } + // Add the command to the command queue: + repl._queue.push( code ); + + // Request to run the command: + drain( repl ); +} + +/** +* Drains a REPL's command queue. +* +* @private +* @param {REPL} repl - REPL instance +* @returns {void} +*/ +function drain( repl ) { + var opts; + var code; + var res; + + if ( repl._queue.length === 0 ) { + debug( 'Command queue is empty.' ); + repl._busy = false; + if ( !repl._closed ) { + displayPrompt( repl, false ); + } + return; + } + if ( repl._busy ) { + debug( 'Waiting on an asynchronous command to finish...' ); + return; + } + debug( 'Evaluating next command...' ); + + // Remove a command from the queue: + code = repl._queue.pop(); + debug( 'Command: %s', code.raw ); + + // TODO: check whether command begins with `await` or `for await` (the latter would allow for updating the last line of output; e.g., an ASCII chart!); if so, then async processing and set `busy` to true; otherwise, assume sync processing + + // Set the (non-standard) properties on the `RegExp` expression object to the cached matches: + restoreRegExpMatches( repl._regexp ); + + // TODO: evaluate and determine whether to print result + opts = { + 'displayErrors': false, + 'breakOnSigint': true // Note: applies only for Node.js versions >=6.3.0 + }; + try { + if ( repl._sandbox ) { + res = code.compiled.runInContext( repl._context, opts ); + } else { + res = code.compiled.runInThisContext( opts ); + } + updateRegExpCache( repl._regexp ); + } catch ( error ) { + updateRegExpCache( repl._regexp ); + + // TODO: handle SIGINT (see https://github.com/nodejs/node/blob/b21e7c7bcf23a2715951e4cd96180e4dbf1dcd4d/lib/repl.js#L581) + + // TODO: check if error is recoverable + debug( 'Error: %s', error.message ); + repl._ostream.write( 'Error: '+error.message+'\n' ); + displayPrompt( repl, false ); + return; + } + if ( code.silent === false && res !== void 0 ) { + repl._ostream.write( inspect( res )+'\n' ); // TODO: pretty printing (can defer to `util.inspect` for now, but will invariably want more control over this later, possibly including default configuration, etc, either at startup, during runtime, or according to an external configuration file) + } + // Cache the result: + repl._ans = res; + + // TODO: if successful, save the command in the history buffer and, if necessary, write to a history file + + // TODO: replace with polyfill + process.nextTick( onTick ); + + /** + * Callback invoked upon the next tick of the event loop. + * + * @private + */ + function onTick() { + drain( repl ); + } +} + +/** +* Clears a REPL's local context. +* +* @private +* @param {REPL} repl - REPL instance +*/ +function clear( repl ) { + debug( 'Clearing the local REPL context...' ); + + // Clear the command queue: + repl._queue.clear(); + + // Clear any command which has been buffered but not yet executed: + repl._cmd.length = 0; + + // Clear the command history: + repl._history.length = 0; + + // When sandboxed, create a new execution context... + if ( repl._sandbox ) { + repl._context = createNewContext( repl ); + repl.emit( 'reset', repl._context ); + } + // Clear an output TTY stream of any previous commands and output: + if ( repl._isTTY ) { + /* + * Clear the entire screen and scrollback history using [ANSI escape sequences][1]. + * + * - `\u001b`: ESC, the escape character + * - `[H`: move cursor to upper left corner + * - `[2J`: clear the entire screen + * - `[3J`: clear the entire screen and delete all lines in the scrollback buffer (note: possible portability issues) + * + * [1]: https://en.wikipedia.org/wiki/ANSI_escape_code + */ + repl._ostream.write( '\u001b[2J\u001b[H\u001b[2J\u001b[3J' ); + } + // Display the command prompt: + displayPrompt( repl, false ); +} + +/** +* Creates a REPL execution context. +* +* @private +* @param {REPL} repl - REPL instance +* @returns {Object} REPL context +*/ +function createNewContext( repl ) { + var context; + + debug( 'Creating REPL execution context...' ); + context = createContext({ + 'sandbox': repl._sandbox, + 'output': repl._ostream + }); + + // Add commands requiring privileged access to internal instance variables: + setNonEnumerableReadOnly( context, 'clear', onClear ); + setNonEnumerableReadOnly( context, 'load', onLoad ); + setNonEnumerableReadOnly( context, 'quit', onQuit ); + + // TODO: add `help` command + // TODO: add `example` command + // TODO: add `namespace` command + // TODO: add `save` command + // TODO: add `recordStart` command + // TODO: add `recordStop` command + // TODO: add `citation` command + // TODO: add `license` command + // TODO: add `copyright` command + // TODO: add `contributors` command + // TODO: add `credits` command + // TODO: add `donate` command + + // Add an accessor for retrieving the result of the last successfully executed command: + setNonEnumerableReadOnlyAccessor( context, 'ans', onAns ); + + return context; + + /** + * Returns the result of the last successfully executed command. + * + * @private + * @returns {*} result + */ + function onAns() { + return repl._ans; + } + + /** + * Clears a REPL's local context. + * + * @private + */ + function onClear() { + clear( repl ); + } + + /** + * Loads and evaluates a JavaScript file line-by-line. + * + * @private + * @param {string} fpath - file path + * @returns {void} + */ + function onLoad( fpath ) { + var err; + if ( !isString( fpath ) ) { + err = new TypeError( 'invalid argument. Must provide a string. Value: `'+fpath+'`.' ); + debug( 'Error: %s', err.message ); + repl._ostream.write( 'Error: '+err.message+'\n' ); + return; + } + debug( 'Loading a file...' ); + repl.load( fpath ); + } + + /** + * Quits a REPL. + * + * @private + */ + function onQuit() { + debug( 'Quitting the REPL...' ); + repl.close(); } - rli.setPrompt( out ); - rli.prompt( preserveCursor ); } /** @@ -130,18 +407,8 @@ function restoreRegExpMatches( cache ) { * // TODO */ function REPL( options ) { - var SAVED_REGEXP_MATCHES; - var istream; - var ostream; - var context; - var history; - var queue; - var busy; var opts; var self; - var cmd; - var ans; - var rli; var err; if ( !( this instanceof REPL ) ) { @@ -176,50 +443,54 @@ function REPL( options ) { EventEmitter.call( this ); // Cache references to the input and output streams: - istream = opts.input; - ostream = opts.output; + setNonEnumerableReadOnly( this, '_istream', opts.input ); + setNonEnumerableReadOnly( this, '_ostream', opts.output ); + + // Cache options: + setNonEnumerableReadOnly( this, '_prompt', opts.prompt ); + setNonEnumerableReadOnly( this, '_isTTY', opts.isTTY ); + setNonEnumerableReadOnly( this, '_sandbox', opts.sandbox ); + + // Initialize an internal flag indicating whether the REPL has been closed: + setNonEnumerable( this, '_closed', false ); - // Initialize an array for storing the command history: - history = []; + // Initialize an internal command queue: + setNonEnumerableReadOnly( this, '_queue', fifo() ); - // Initialize a "buffer" for storing the current command: - cmd = []; + // Initialize an internal buffer for storing the command history: + setNonEnumerableReadOnly( this, '_history', [] ); - // Initialize a flag indicating whether the REPL is currently busy with asynchronous processing: - busy = false; + // Initialize an internal buffer for storing the current command: + setNonEnumerableReadOnly( this, '_cmd', [] ); - // Initialize an array for saving regular expression matches between command evaluations: - SAVED_REGEXP_MATCHES = [ '', '', '', '', '', '', '', '', '', '' ]; + // Initialize an internal buffer for saving regular expression matches between command evaluations: + setNonEnumerableReadOnly( this, '_regexp', [ '', '', '', '', '', '', '', '', '', '' ] ); + + // Initialize an internal flag indicating whether the REPL is currently busy with asynchronous processing: + setNonEnumerable( this, '_busy', false ); + + // Initialize an internal variable for caching the result of the last successfully evaluated command: + setNonEnumerable( this, '_ans', void 0 ); // Create an internal readline interface: debug( 'Creating readline interface...' ); - rli = readline.createInterface({ - 'input': istream, - 'output': ostream, + setNonEnumerableReadOnly( this, '_rli', readline.createInterface({ + 'input': this._istream, + 'output': this._ostream, 'terminal': opts.isTTY, 'prompt': opts.prompt - }); - rli.on( 'close', onClose ); - rli.on( 'line', onLine ); - - // Cache a reference to the readline interface: - setNonEnumerableReadOnly( this, '_rli', rli ); - - // Create an internal flag indicating whether the REPL has been closed: - setNonEnumerable( this, '_closed', false ); + })); + this._rli.on( 'close', onClose ); + this._rli.on( 'line', onLine ); - // Initialize a command queue: - queue = fifo(); - setNonEnumerableReadOnly( this, '_queue', queue ); + // Create a REPL execution context: + setNonEnumerable( this, '_context', createNewContext( this ) ); // Add a public method for clearing a REPL: setNonEnumerableReadOnly( this, 'clear', clear ); - // Create a REPL execution context: - createNewContext(); - // Write a welcome message: - ostream.write( opts.welcome ); + this._ostream.write( opts.welcome ); // TODO: check whether to synchronously initialize a REPL history file @@ -227,78 +498,18 @@ function REPL( options ) { if ( opts.load ) { this.load( opts.load ); } else { - displayPrompt( rli, cmd, opts.prompt, false ); + displayPrompt( this, false ); } return this; /** - * Callback invoked upon receiving a readline interface "line" event. + * Callback invoked upon a readline interface "line" event. * * @private * @param {string} line - line data - * @returns {void} */ function onLine( line ) { - var isWrapped; - var script; - var sopts; - var code; - - debug( 'Line: %s', line ); - - // Removing leading and trailing whitespace: - line = trim( line ); - - // TODO: check if the line is valid JavaScript syntax; if yes, then proceed; otherwise, buffer the command in `cmd` buffer until ready to execute (e.g., when providing multi-line input) - - sopts = { - 'filename': '', - 'lineOffset': 0 - }; - code = { - 'raw': line - }; - - // Check for commands like object literals (e.g., `{'a':1}`), which we want to be evaluated as expressions, rather than blocks... - if ( RE_OPENING_BRACE.test( line ) && RE_CLOSING_BRACE.test( line ) ) { - // FIXME: we need to actually parse into an AST here and check if the last "expression" begins and ends with braces (e.g., `1+1; {'a':1}`); if so, we need to wrap the last expression in parentheses - // FIXME: the above also fails to account for `{'a':1};`, which ends in a semicolon and not a brace - // FIXME: the above also fails to account for expressions such as variable assignments (e.g., `var v = [1,2,3]`), where we may want to see the assigned value - line = '(' + line + ')\n'; - isWrapped = true; - } - // Attempt to compile the command... - while ( true ) { - try { - if ( RE_WHITESPACE.test( line ) ) { - script = new vm.Script( line, sopts ); - code.silent = true; - } else { - // Note: `void 0` ensures that the compiled script does not return the string `'use strict'` when provided commands (statements/declarations) which do not return a value (e.g., `{}`): - script = new vm.Script( '\'use strict\'; void 0;\n'+line, sopts ); - code.silent = line.charCodeAt( line.length-1 ) === SEMICOLON; // eslint-disable-line max-len - } - code.compiled = script; - } catch ( error ) { - // If we previously wrapped the command, unwrap and try again... - if ( isWrapped ) { - isWrapped = false; - line = code.raw; - continue; - } - // TODO: check if error is recoverable? And if so, update the command buffer; otherwise, write error message to console and display prompt. - debug( 'Error: %s', error.message ); - ostream.write( 'Error: '+error.message+'\n' ); - displayPrompt( rli, cmd, opts.prompt, false ); - return; - } - break; - } - // Add the command to the command queue: - queue.push( code ); - - // Request to run the command: - drain(); + processLine( self, line ); } /** @@ -311,193 +522,6 @@ function REPL( options ) { debug( 'Exiting the REPL...' ); self.emit( 'exit' ); } - - /** - * Creates a REPL execution context. - * - * @private - * @returns {Object} REPL context - */ - function createNewContext() { - debug( 'Creating REPL execution context...' ); - - // Create a new context: - context = createContext({ - 'sandbox': opts.sandbox, - 'output': ostream - }); - - // Add commands requiring privileged access to internal instance variables: - setNonEnumerableReadOnly( context, 'clear', clear ); - setNonEnumerableReadOnly( context, 'load', load ); - setNonEnumerableReadOnly( context, 'quit', quit ); - - // TODO: add `help` command - // TODO: add `example` command - // TODO: add `namespace` command - // TODO: add `save` command - // TODO: add `recordStart` command - // TODO: add `recordStop` command - // TODO: add `citation` command - // TODO: add `license` command - // TODO: add `copyright` command - // TODO: add `contributors` command - // TODO: add `credits` command - // TODO: add `donate` command - - // Add an accessor for retrieving the result of the last successfully executed command: - setNonEnumerableReadOnlyAccessor( context, 'ans', getLastAnswer ); - - return context; - } - - /** - * Returns the result of the last successfully executed command. - * - * @private - * @returns {*} result - */ - function getLastAnswer() { - return ans; - } - - /** - * Drains the command queue. - * - * @private - * @returns {void} - */ - function drain() { - var sopts; - var code; - var res; - - if ( queue.length === 0 ) { - debug( 'Command queue is empty.' ); - busy = false; - if ( !self._closed ) { // eslint-disable-line no-underscore-dangle - displayPrompt( rli, cmd, opts.prompt, false ); - } - return; - } - if ( busy ) { - debug( 'Waiting on an asynchronous command to finish...' ); - return; - } - debug( 'Evaluating next command...' ); - - // Remove a command from the queue: - code = queue.pop(); - debug( 'Command: %s', code.raw ); - - // TODO: check whether command begins with `await` or `for await` (the latter would allow for updating the last line of output; e.g., an ASCII chart!); if so, then async processing and set `busy` to true; otherwise, assume sync processing - - // Set the (non-standard) properties on the `RegExp` expression object to the cached matches: - restoreRegExpMatches( SAVED_REGEXP_MATCHES ); - - // TODO: evaluate and determine whether to print result - sopts = { - 'displayErrors': false, - 'breakOnSigint': true // Note: applies only for Node.js versions >=6.3.0 - }; - try { - if ( opts.sandbox ) { - res = code.compiled.runInContext( context, sopts ); - } else { - res = code.compiled.runInThisContext( sopts ); - } - updateRegExpCache( SAVED_REGEXP_MATCHES ); - } catch ( error ) { - updateRegExpCache( SAVED_REGEXP_MATCHES ); - - // TODO: handle SIGINT (see https://github.com/nodejs/node/blob/b21e7c7bcf23a2715951e4cd96180e4dbf1dcd4d/lib/repl.js#L581) - - // TODO: check if error is recoverable - debug( 'Error: %s', error.message ); - ostream.write( 'Error: '+error.message+'\n' ); - displayPrompt( rli, cmd, opts.prompt, false ); - return; - } - if ( code.silent === false && res !== void 0 ) { - ostream.write( inspect( res )+'\n' ); // TODO: pretty printing (can defer to `util.inspect` for now, but will invariably want more control over this later, possibly including default configuration, etc, either at startup, during runtime, or according to an external configuration file) - } - // Cache the result: - ans = res; - - // TODO: if successful, save the command in the history buffer and, if necessary, write to a history file - - // TODO: replace with polyfill - process.nextTick( drain ); - } - - /** - * Clears the local context. - * - * @private - */ - function clear() { - debug( 'Clearing the local REPL context...' ); - - // Clear the command queue: - queue.clear(); - - // Clear any command which has been buffered but not yet executed: - cmd.length = 0; - - // Clear the command history: - history.length = 0; - - // When sandboxed, create a new execution context... - if ( opts.sandbox ) { - context = createNewContext(); - self.emit( 'reset', context ); - } - // Clear an output TTY stream of any previous commands and output: - if ( opts.isTTY ) { - /* - * Clear the entire screen and scrollback history using [ANSI escape sequences][1]. - * - * - `\u001b`: ESC, the escape character - * - `[H`: move cursor to upper left corner - * - `[2J`: clear the entire screen - * - `[3J`: clear the entire screen and delete all lines in the scrollback buffer - * - * [1]: https://en.wikipedia.org/wiki/ANSI_escape_code - */ - ostream.write( '\u001b[2J\u001b[H\u001b[2J\u001b[3J' ); - } - // Display the command prompt: - displayPrompt( rli, cmd, opts.prompt, false ); - } - - /** - * Loads and evaluates a JavaScript file line-by-line. - * - * @private - * @param {string} fpath - file path - * @returns {void} - */ - function load( fpath ) { - var err; - if ( !isString( fpath ) ) { - err = new TypeError( 'invalid argument. Must provide a string. Value: `'+fpath+'`.' ); - debug( 'Error: %s', err.message ); - ostream.write( 'Error: '+err.message+'\n' ); - return; - } - debug( 'Loading a file...' ); - self.load( fpath ); - } - - /** - * Quits a REPL. - * - * @private - */ - function quit() { - debug( 'Quitting the REPL...' ); - self.close(); - } } /* @@ -579,7 +603,7 @@ setNonEnumerableReadOnly( REPL.prototype, 'close', function close() { */ function onTick() { debug( 'Closing the readline interface...' ); - self._rli.close(); // eslint-disable-line no-underscore-dangle + self._rli.close(); } }); From 34458aa4d99eca86bc8342babe46f47069344559 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 01:19:29 -0700 Subject: [PATCH 023/142] Move method to prototype --- .../@stdlib/repl/ctor/lib/main.js | 22 ++++++++++++++----- 1 file changed, 16 insertions(+), 6 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index 836ac358f9ca..5034bc6ee100 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -451,9 +451,6 @@ function REPL( options ) { setNonEnumerableReadOnly( this, '_isTTY', opts.isTTY ); setNonEnumerableReadOnly( this, '_sandbox', opts.sandbox ); - // Initialize an internal flag indicating whether the REPL has been closed: - setNonEnumerable( this, '_closed', false ); - // Initialize an internal command queue: setNonEnumerableReadOnly( this, '_queue', fifo() ); @@ -466,6 +463,9 @@ function REPL( options ) { // Initialize an internal buffer for saving regular expression matches between command evaluations: setNonEnumerableReadOnly( this, '_regexp', [ '', '', '', '', '', '', '', '', '', '' ] ); + // Initialize an internal flag indicating whether the REPL has been closed: + setNonEnumerable( this, '_closed', false ); + // Initialize an internal flag indicating whether the REPL is currently busy with asynchronous processing: setNonEnumerable( this, '_busy', false ); @@ -486,9 +486,6 @@ function REPL( options ) { // Create a REPL execution context: setNonEnumerable( this, '_context', createNewContext( this ) ); - // Add a public method for clearing a REPL: - setNonEnumerableReadOnly( this, 'clear', clear ); - // Write a welcome message: this._ostream.write( opts.welcome ); @@ -570,6 +567,19 @@ setNonEnumerableReadOnly( REPL.prototype, 'load', function load( fpath ) { return this; }); +/** +* Clears a REPL's local context. +* +* @name clear +* @memberof REPL.prototype +* @type {Function} +* @returns {REPL} REPL instance +*/ +setNonEnumerableReadOnly( REPL.prototype, 'clear', function onClear() { + clear( this ); + return this; +}); + /** * Closes a REPL. * From bc2e756b02ed835b44cd4d4a791963a992158021 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 01:25:47 -0700 Subject: [PATCH 024/142] Prevent operations on a closed REPL --- lib/node_modules/@stdlib/repl/ctor/lib/main.js | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index 5034bc6ee100..3dcca5b42400 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -537,12 +537,16 @@ inherit( REPL, EventEmitter ); * @memberof REPL.prototype * @type {Function} * @param {string} fpath - file path +* @throws {Error} cannot load a file into a closed REPL * @throws {TypeError} must provide a string * @returns {REPL} REPL instance */ setNonEnumerableReadOnly( REPL.prototype, 'load', function load( fpath ) { var file; var i; + if ( this._closed ) { + throw new Error( 'invalid operation. Cannot load a file into a REPL which has already closed.' ); + } if ( !isString( fpath ) ) { throw new TypeError( 'invalid argument. Must provide a string. Value: `' + fpath + '`.' ); } @@ -573,9 +577,13 @@ setNonEnumerableReadOnly( REPL.prototype, 'load', function load( fpath ) { * @name clear * @memberof REPL.prototype * @type {Function} +* @throws {Error} cannot clear a closed REPL * @returns {REPL} REPL instance */ setNonEnumerableReadOnly( REPL.prototype, 'clear', function onClear() { + if ( this._closed ) { + throw new Error( 'invalid operation. Cannot clear a REPL which has already closed.' ); + } clear( this ); return this; }); From c25707cb36734d4e3625bd5317baa08d9455736a Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 01:52:16 -0700 Subject: [PATCH 025/142] Move functions to separate files --- .../@stdlib/repl/ctor/lib/clear.js | 81 ++++ .../repl/ctor/lib/create_new_context.js | 130 +++++++ .../@stdlib/repl/ctor/lib/display_prompt.js | 47 +++ .../@stdlib/repl/ctor/lib/drain.js | 155 ++++++++ .../@stdlib/repl/ctor/lib/main.js | 347 +----------------- .../@stdlib/repl/ctor/lib/process_line.js | 117 ++++++ 6 files changed, 534 insertions(+), 343 deletions(-) create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/clear.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/display_prompt.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/drain.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/process_line.js diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/clear.js b/lib/node_modules/@stdlib/repl/ctor/lib/clear.js new file mode 100644 index 000000000000..9e7df95a1646 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/clear.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable no-underscore-dangle */ + +'use strict'; + +// MODULES // + +var logger = require( 'debug' ); +var createNewContext = require( './create_new_context.js' ); +var displayPrompt = require( './display_prompt.js' ); + + +// VARIABLES // + +var debug = logger( 'repl:clear' ); + + +// MAIN // + +/** +* Clears a REPL's local context. +* +* @private +* @param {REPL} repl - REPL instance +*/ +function clear( repl ) { + debug( 'Clearing the local REPL context...' ); + + // Clear the command queue: + repl._queue.clear(); + + // Clear any command which has been buffered but not yet executed: + repl._cmd.length = 0; + + // Clear the command history: + repl._history.length = 0; + + // When sandboxed, create a new execution context... + if ( repl._sandbox ) { + repl._context = createNewContext( repl ); + repl.emit( 'reset', repl._context ); + } + // Clear an output TTY stream of any previous commands and output: + if ( repl._isTTY ) { + /* + * Clear the entire screen and scrollback history using [ANSI escape sequences][1]. + * + * - `\u001b`: ESC, the escape character + * - `[H`: move cursor to upper left corner + * - `[2J`: clear the entire screen + * - `[3J`: clear the entire screen and delete all lines in the scrollback buffer (note: possible portability issues) + * + * [1]: https://en.wikipedia.org/wiki/ANSI_escape_code + */ + repl._ostream.write( '\u001b[2J\u001b[H\u001b[2J\u001b[3J' ); + } + // Display the command prompt: + displayPrompt( repl, false ); +} + + +// EXPORTS // + +module.exports = clear; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js new file mode 100644 index 000000000000..c156375986d1 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js @@ -0,0 +1,130 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable no-underscore-dangle */ + +'use strict'; + +// MODULES // + +var logger = require( 'debug' ); +var setNonEnumerableReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var setNonEnumerableReadOnlyAccessor = require( '@stdlib/utils/define-nonenumerable-read-only-accessor' ); // eslint-disable-line id-length +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var createContext = require( './create_context.js' ); + + +// VARIABLES // + +var debug = logger( 'repl:context' ); + + +// MAIN // + +/** +* Creates a REPL execution context. +* +* @private +* @param {REPL} repl - REPL instance +* @returns {Object} REPL context +*/ +function createNewContext( repl ) { + var context; + + debug( 'Creating REPL execution context...' ); + context = createContext({ + 'sandbox': repl._sandbox, + 'output': repl._ostream + }); + + // Add commands requiring privileged access to internal instance variables: + setNonEnumerableReadOnly( context, 'clear', onClear ); + setNonEnumerableReadOnly( context, 'load', onLoad ); + setNonEnumerableReadOnly( context, 'quit', onQuit ); + + // TODO: add `help` command + // TODO: add `example` command + // TODO: add `namespace` command + // TODO: add `save` command + // TODO: add `recordStart` command + // TODO: add `recordStop` command + // TODO: add `citation` command + // TODO: add `license` command + // TODO: add `copyright` command + // TODO: add `contributors` command + // TODO: add `credits` command + // TODO: add `donate` command + + // Add an accessor for retrieving the result of the last successfully executed command: + setNonEnumerableReadOnlyAccessor( context, 'ans', onAns ); + + return context; + + /** + * Returns the result of the last successfully executed command. + * + * @private + * @returns {*} result + */ + function onAns() { + return repl._ans; + } + + /** + * Clears a REPL's local context. + * + * @private + */ + function onClear() { + repl.clear(); + } + + /** + * Loads and evaluates a JavaScript file line-by-line. + * + * @private + * @param {string} fpath - file path + * @returns {void} + */ + function onLoad( fpath ) { + var err; + if ( !isString( fpath ) ) { + err = new TypeError( 'invalid argument. Must provide a string. Value: `'+fpath+'`.' ); + debug( 'Error: %s', err.message ); + repl._ostream.write( 'Error: '+err.message+'\n' ); + return; + } + debug( 'Loading a file...' ); + repl.load( fpath ); + } + + /** + * Quits a REPL. + * + * @private + */ + function onQuit() { + debug( 'Quitting the REPL...' ); + repl.close(); + } +} + + +// EXPORTS // + +module.exports = createNewContext; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/display_prompt.js b/lib/node_modules/@stdlib/repl/ctor/lib/display_prompt.js new file mode 100644 index 000000000000..3e625f98924c --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/display_prompt.js @@ -0,0 +1,47 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable no-underscore-dangle */ + +'use strict'; + +// MAIN // + +/** +* Displays a command prompt. +* +* @private +* @param {REPL} repl - REPL instance +* @param {boolean} [preserveCursor=false] - boolean indicating whether to preserve the cursor position +*/ +function displayPrompt( repl, preserveCursor ) { + var prompt; + if ( repl._cmd.length ) { + // TODO: determine indentation level (use spaces) + prompt = ''; + } else { + prompt = repl._prompt; + } + repl._rli.setPrompt( prompt ); + repl._rli.prompt( preserveCursor ); +} + + +// EXPORTS // + +module.exports = displayPrompt; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/drain.js b/lib/node_modules/@stdlib/repl/ctor/lib/drain.js new file mode 100644 index 000000000000..55dce0f81cea --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/drain.js @@ -0,0 +1,155 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable no-underscore-dangle */ + +'use strict'; + +// MODULES // + +var inspect = require( 'util' ).inspect; +var logger = require( 'debug' ); +var displayPrompt = require( './display_prompt.js' ); + + +// VARIABLES // + +var debug = logger( 'repl:drain' ); + +/* +* In certain JavaScript engines (e.g., V8, SpiderMonkey), the global `RegExp` object has ([non-standard][1]) static, read-only properties (`$1`, `$2`, ..., `$9`) with cached substring matches. In order to preserve these matches between command evaluations, we need to capture and subsequently restore them prior to evaluation. +* +* [1]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/RegExp/n +*/ +var SEP_REGEXP_MATCHES = '\u0000\u0000\u0000'; +var RE_REGEXP_MATCHES = new RegExp( [ '^', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)$' ].join( SEP_REGEXP_MATCHES ) ); + + +// FUNCTIONS // + +/** +* Updates the cache of saved regular expression substring matches. +* +* @private +* @param {StringArray} cache - list of previously saved substring matches +* @returns {StringArray} cache +*/ +function updateRegExpCache( cache ) { + var i; + for ( i = 1; i < cache.length; i++ ) { + cache[ i ] = RegExp[ '$'+i ]; + } + return cache; +} + +/** +* Restores the (non-standard) properties on the `RegExp` expression object to the cached matches. +* +* @private +* @param {StringArray} cache - list of previously saved substring matches +*/ +function restoreRegExpMatches( cache ) { + RE_REGEXP_MATCHES.test( cache.join( SEP_REGEXP_MATCHES ) ); +} + + +// MAIN // + +/** +* Drains a REPL's command queue. +* +* @private +* @param {REPL} repl - REPL instance +* @returns {void} +*/ +function drain( repl ) { + var opts; + var code; + var res; + + if ( repl._queue.length === 0 ) { + debug( 'Command queue is empty.' ); + repl._busy = false; + if ( !repl._closed ) { + displayPrompt( repl, false ); + } + return; + } + if ( repl._busy ) { + debug( 'Waiting on an asynchronous command to finish...' ); + return; + } + debug( 'Evaluating next command...' ); + + // Remove a command from the queue: + code = repl._queue.pop(); + debug( 'Command: %s', code.raw ); + + // TODO: check whether command begins with `await` or `for await` (the latter would allow for updating the last line of output; e.g., an ASCII chart!); if so, then async processing and set `busy` to true; otherwise, assume sync processing + + // Set the (non-standard) properties on the `RegExp` expression object to the cached matches: + restoreRegExpMatches( repl._regexp ); + + // TODO: evaluate and determine whether to print result + opts = { + 'displayErrors': false, + 'breakOnSigint': true // Note: applies only for Node.js versions >=6.3.0 + }; + try { + if ( repl._sandbox ) { + res = code.compiled.runInContext( repl._context, opts ); + } else { + res = code.compiled.runInThisContext( opts ); + } + updateRegExpCache( repl._regexp ); + } catch ( error ) { + updateRegExpCache( repl._regexp ); + + // TODO: handle SIGINT (see https://github.com/nodejs/node/blob/b21e7c7bcf23a2715951e4cd96180e4dbf1dcd4d/lib/repl.js#L581) + + // TODO: check if error is recoverable + debug( 'Error: %s', error.message ); + repl._ostream.write( 'Error: '+error.message+'\n' ); + displayPrompt( repl, false ); + return; + } + if ( code.silent === false && res !== void 0 ) { + repl._ostream.write( inspect( res )+'\n' ); // TODO: pretty printing (can defer to `util.inspect` for now, but will invariably want more control over this later, possibly including default configuration, etc, either at startup, during runtime, or according to an external configuration file) + } + // Cache the result: + repl._ans = res; + + // TODO: if successful, save the command in the history buffer and, if necessary, write to a history file + + // TODO: replace with polyfill + process.nextTick( onTick ); + + /** + * Callback invoked upon the next tick of the event loop. + * + * @private + */ + function onTick() { + drain( repl ); + } +} + + +// EXPORTS // + +module.exports = drain; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index 3dcca5b42400..906cb4d8eacf 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -25,365 +25,26 @@ var EventEmitter = require( 'events' ).EventEmitter; var readline = require( 'readline' ); var resolve = require( 'path' ).resolve; -var vm = require( 'vm' ); -var inspect = require( 'util' ).inspect; var logger = require( 'debug' ); var inherit = require( '@stdlib/utils/inherit' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var setNonEnumerable = require( '@stdlib/utils/define-nonenumerable-property' ); var setNonEnumerableReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); -var setNonEnumerableReadOnlyAccessor = require( '@stdlib/utils/define-nonenumerable-read-only-accessor' ); // eslint-disable-line id-length -var trim = require( '@stdlib/string/trim' ); var cwd = require( '@stdlib/process/cwd' ); var readFileSync = require( '@stdlib/fs/read-file' ).sync; var RE_EOL = require( '@stdlib/regexp/eol' ); var fifo = require( '@stdlib/utils/fifo' ); var validate = require( './validate.js' ); var defaults = require( './defaults.js' ); -var createContext = require( './create_context.js' ); +var displayPrompt = require( './display_prompt.js' ); +var createNewContext = require( './create_new_context.js' ); +var processLine = require( './process_line.js' ); +var clear = require( './clear.js' ); // VARIABLES // var debug = logger( 'repl' ); -var SEMICOLON = 59; // character code -var RE_OPENING_BRACE = /^\s*\{/; -var RE_CLOSING_BRACE = /\}\s*$/; -var RE_WHITESPACE = /^\s*$/; - -/* -* In certain JavaScript engines (e.g., V8, SpiderMonkey), the global `RegExp` object has ([non-standard][1]) static, read-only properties (`$1`, `$2`, ..., `$9`) with cached substring matches. In order to preserve these matches between command evaluations, we need to capture and subsequently restore them prior to evaluation. -* -* [1]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/RegExp/n -*/ -var SEP_REGEXP_MATCHES = '\u0000\u0000\u0000'; -var RE_REGEXP_MATCHES = new RegExp( [ '^', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)', '(.*)$' ].join( SEP_REGEXP_MATCHES ) ); - - -// FUNCTIONS // - -/** -* Displays a command prompt. -* -* @private -* @param {REPL} repl - REPL instance -* @param {boolean} [preserveCursor=false] - boolean indicating whether to preserve the cursor position -*/ -function displayPrompt( repl, preserveCursor ) { - var prompt; - if ( repl._cmd.length ) { - // TODO: determine indentation level (use spaces) - prompt = ''; - } else { - prompt = repl._prompt; - } - repl._rli.setPrompt( prompt ); - repl._rli.prompt( preserveCursor ); -} - -/** -* Processes input line data. -* -* @private -* @param {REPL} repl - REPL instance -* @param {string} line - line data -* @returns {void} -*/ -function processLine( repl, line ) { - var isWrapped; - var script; - var opts; - var code; - - debug( 'Line: %s', line ); - - // Removing leading and trailing whitespace: - line = trim( line ); - - // TODO: check if the line is valid JavaScript syntax; if yes, then proceed; otherwise, buffer the command in `cmd` buffer until ready to execute (e.g., when providing multi-line input) - - opts = { - 'filename': '', - 'lineOffset': 0 - }; - code = { - 'raw': line - }; - - // Check for commands like object literals (e.g., `{'a':1}`), which we want to be evaluated as expressions, rather than blocks... - if ( RE_OPENING_BRACE.test( line ) && RE_CLOSING_BRACE.test( line ) ) { - // FIXME: we need to actually parse into an AST here and check if the last "expression" begins and ends with braces (e.g., `1+1; {'a':1}`); if so, we need to wrap the last expression in parentheses - // FIXME: the above also fails to account for `{'a':1};`, which ends in a semicolon and not a brace - // FIXME: the above also fails to account for expressions such as variable assignments (e.g., `var v = [1,2,3]`), where we may want to see the assigned value - line = '(' + line + ')\n'; - isWrapped = true; - } - // Attempt to compile the command... - while ( true ) { - try { - if ( RE_WHITESPACE.test( line ) ) { - script = new vm.Script( line, opts ); - code.silent = true; - } else { - // Note: `void 0` ensures that the compiled script does not return the string `'use strict'` when provided commands (statements/declarations) which do not return a value (e.g., `{}`): - script = new vm.Script( '\'use strict\'; void 0;\n'+line, opts ); - code.silent = line.charCodeAt( line.length-1 ) === SEMICOLON; // eslint-disable-line max-len - } - code.compiled = script; - } catch ( error ) { - // If we previously wrapped the command, unwrap and try again... - if ( isWrapped ) { - isWrapped = false; - line = code.raw; - continue; - } - // TODO: check if error is recoverable? And if so, update the command buffer; otherwise, write error message to console and display prompt. - debug( 'Error: %s', error.message ); - repl._ostream.write( 'Error: '+error.message+'\n' ); - displayPrompt( repl, false ); - return; - } - break; - } - // Add the command to the command queue: - repl._queue.push( code ); - - // Request to run the command: - drain( repl ); -} - -/** -* Drains a REPL's command queue. -* -* @private -* @param {REPL} repl - REPL instance -* @returns {void} -*/ -function drain( repl ) { - var opts; - var code; - var res; - - if ( repl._queue.length === 0 ) { - debug( 'Command queue is empty.' ); - repl._busy = false; - if ( !repl._closed ) { - displayPrompt( repl, false ); - } - return; - } - if ( repl._busy ) { - debug( 'Waiting on an asynchronous command to finish...' ); - return; - } - debug( 'Evaluating next command...' ); - - // Remove a command from the queue: - code = repl._queue.pop(); - debug( 'Command: %s', code.raw ); - - // TODO: check whether command begins with `await` or `for await` (the latter would allow for updating the last line of output; e.g., an ASCII chart!); if so, then async processing and set `busy` to true; otherwise, assume sync processing - - // Set the (non-standard) properties on the `RegExp` expression object to the cached matches: - restoreRegExpMatches( repl._regexp ); - - // TODO: evaluate and determine whether to print result - opts = { - 'displayErrors': false, - 'breakOnSigint': true // Note: applies only for Node.js versions >=6.3.0 - }; - try { - if ( repl._sandbox ) { - res = code.compiled.runInContext( repl._context, opts ); - } else { - res = code.compiled.runInThisContext( opts ); - } - updateRegExpCache( repl._regexp ); - } catch ( error ) { - updateRegExpCache( repl._regexp ); - - // TODO: handle SIGINT (see https://github.com/nodejs/node/blob/b21e7c7bcf23a2715951e4cd96180e4dbf1dcd4d/lib/repl.js#L581) - - // TODO: check if error is recoverable - debug( 'Error: %s', error.message ); - repl._ostream.write( 'Error: '+error.message+'\n' ); - displayPrompt( repl, false ); - return; - } - if ( code.silent === false && res !== void 0 ) { - repl._ostream.write( inspect( res )+'\n' ); // TODO: pretty printing (can defer to `util.inspect` for now, but will invariably want more control over this later, possibly including default configuration, etc, either at startup, during runtime, or according to an external configuration file) - } - // Cache the result: - repl._ans = res; - - // TODO: if successful, save the command in the history buffer and, if necessary, write to a history file - - // TODO: replace with polyfill - process.nextTick( onTick ); - - /** - * Callback invoked upon the next tick of the event loop. - * - * @private - */ - function onTick() { - drain( repl ); - } -} - -/** -* Clears a REPL's local context. -* -* @private -* @param {REPL} repl - REPL instance -*/ -function clear( repl ) { - debug( 'Clearing the local REPL context...' ); - - // Clear the command queue: - repl._queue.clear(); - - // Clear any command which has been buffered but not yet executed: - repl._cmd.length = 0; - - // Clear the command history: - repl._history.length = 0; - - // When sandboxed, create a new execution context... - if ( repl._sandbox ) { - repl._context = createNewContext( repl ); - repl.emit( 'reset', repl._context ); - } - // Clear an output TTY stream of any previous commands and output: - if ( repl._isTTY ) { - /* - * Clear the entire screen and scrollback history using [ANSI escape sequences][1]. - * - * - `\u001b`: ESC, the escape character - * - `[H`: move cursor to upper left corner - * - `[2J`: clear the entire screen - * - `[3J`: clear the entire screen and delete all lines in the scrollback buffer (note: possible portability issues) - * - * [1]: https://en.wikipedia.org/wiki/ANSI_escape_code - */ - repl._ostream.write( '\u001b[2J\u001b[H\u001b[2J\u001b[3J' ); - } - // Display the command prompt: - displayPrompt( repl, false ); -} - -/** -* Creates a REPL execution context. -* -* @private -* @param {REPL} repl - REPL instance -* @returns {Object} REPL context -*/ -function createNewContext( repl ) { - var context; - - debug( 'Creating REPL execution context...' ); - context = createContext({ - 'sandbox': repl._sandbox, - 'output': repl._ostream - }); - - // Add commands requiring privileged access to internal instance variables: - setNonEnumerableReadOnly( context, 'clear', onClear ); - setNonEnumerableReadOnly( context, 'load', onLoad ); - setNonEnumerableReadOnly( context, 'quit', onQuit ); - - // TODO: add `help` command - // TODO: add `example` command - // TODO: add `namespace` command - // TODO: add `save` command - // TODO: add `recordStart` command - // TODO: add `recordStop` command - // TODO: add `citation` command - // TODO: add `license` command - // TODO: add `copyright` command - // TODO: add `contributors` command - // TODO: add `credits` command - // TODO: add `donate` command - - // Add an accessor for retrieving the result of the last successfully executed command: - setNonEnumerableReadOnlyAccessor( context, 'ans', onAns ); - - return context; - - /** - * Returns the result of the last successfully executed command. - * - * @private - * @returns {*} result - */ - function onAns() { - return repl._ans; - } - - /** - * Clears a REPL's local context. - * - * @private - */ - function onClear() { - clear( repl ); - } - - /** - * Loads and evaluates a JavaScript file line-by-line. - * - * @private - * @param {string} fpath - file path - * @returns {void} - */ - function onLoad( fpath ) { - var err; - if ( !isString( fpath ) ) { - err = new TypeError( 'invalid argument. Must provide a string. Value: `'+fpath+'`.' ); - debug( 'Error: %s', err.message ); - repl._ostream.write( 'Error: '+err.message+'\n' ); - return; - } - debug( 'Loading a file...' ); - repl.load( fpath ); - } - - /** - * Quits a REPL. - * - * @private - */ - function onQuit() { - debug( 'Quitting the REPL...' ); - repl.close(); - } -} - -/** -* Updates the cache of saved regular expression substring matches. -* -* @private -* @param {StringArray} cache - list of previously saved substring matches -* @returns {StringArray} cache -*/ -function updateRegExpCache( cache ) { - var i; - for ( i = 1; i < cache.length; i++ ) { - cache[ i ] = RegExp[ '$'+i ]; - } - return cache; -} - -/** -* Restores the (non-standard) properties on the `RegExp` expression object to the cached matches. -* -* @private -* @param {StringArray} cache - list of previously saved substring matches -*/ -function restoreRegExpMatches( cache ) { - RE_REGEXP_MATCHES.test( cache.join( SEP_REGEXP_MATCHES ) ); -} // MAIN // diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/process_line.js b/lib/node_modules/@stdlib/repl/ctor/lib/process_line.js new file mode 100644 index 000000000000..176fdd63c5d9 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/process_line.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable no-underscore-dangle */ + +'use strict'; + +// MODULES // + +var vm = require( 'vm' ); +var logger = require( 'debug' ); +var trim = require( '@stdlib/string/trim' ); +var displayPrompt = require( './display_prompt.js' ); +var drain = require( './drain.js' ); + + +// VARIABLES // + +var debug = logger( 'repl:line' ); +var SEMICOLON = 59; // character code +var RE_OPENING_BRACE = /^\s*\{/; +var RE_CLOSING_BRACE = /\}\s*$/; +var RE_WHITESPACE = /^\s*$/; + + +// MAIN // + +/** +* Processes input line data. +* +* @private +* @param {REPL} repl - REPL instance +* @param {string} line - line data +* @returns {void} +*/ +function processLine( repl, line ) { + var isWrapped; + var script; + var opts; + var code; + + debug( 'Line: %s', line ); + + // Removing leading and trailing whitespace: + line = trim( line ); + + // TODO: check if the line is valid JavaScript syntax; if yes, then proceed; otherwise, buffer the command in `cmd` buffer until ready to execute (e.g., when providing multi-line input) + + opts = { + 'filename': '', + 'lineOffset': 0 + }; + code = { + 'raw': line + }; + + // Check for commands like object literals (e.g., `{'a':1}`), which we want to be evaluated as expressions, rather than blocks... + if ( RE_OPENING_BRACE.test( line ) && RE_CLOSING_BRACE.test( line ) ) { + // FIXME: we need to actually parse into an AST here and check if the last "expression" begins and ends with braces (e.g., `1+1; {'a':1}`); if so, we need to wrap the last expression in parentheses + // FIXME: the above also fails to account for `{'a':1};`, which ends in a semicolon and not a brace + // FIXME: the above also fails to account for expressions such as variable assignments (e.g., `var v = [1,2,3]`), where we may want to see the assigned value + line = '(' + line + ')\n'; + isWrapped = true; + } + // Attempt to compile the command... + while ( true ) { + try { + if ( RE_WHITESPACE.test( line ) ) { + script = new vm.Script( line, opts ); + code.silent = true; + } else { + // Note: `void 0` ensures that the compiled script does not return the string `'use strict'` when provided commands (statements/declarations) which do not return a value (e.g., `{}`): + script = new vm.Script( '\'use strict\'; void 0;\n'+line, opts ); + code.silent = line.charCodeAt( line.length-1 ) === SEMICOLON; // eslint-disable-line max-len + } + code.compiled = script; + } catch ( error ) { + // If we previously wrapped the command, unwrap and try again... + if ( isWrapped ) { + isWrapped = false; + line = code.raw; + continue; + } + // TODO: check if error is recoverable? And if so, update the command buffer; otherwise, write error message to console and display prompt. + debug( 'Error: %s', error.message ); + repl._ostream.write( 'Error: '+error.message+'\n' ); + displayPrompt( repl, false ); + return; + } + break; + } + // Add the command to the command queue: + repl._queue.push( code ); + + // Request to run the command: + drain( repl ); +} + + +// EXPORTS // + +module.exports = processLine; From 1d48003ee7ab14b47b0d8e83af5f1c1233d02110 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 02:01:59 -0700 Subject: [PATCH 026/142] Import only the used method --- lib/node_modules/@stdlib/repl/ctor/lib/main.js | 11 ++++++----- 1 file changed, 6 insertions(+), 5 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index 906cb4d8eacf..bbb08f9a8d21 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -23,7 +23,7 @@ // MODULES // var EventEmitter = require( 'events' ).EventEmitter; -var readline = require( 'readline' ); +var readline = require( 'readline' ).createInterface; var resolve = require( 'path' ).resolve; var logger = require( 'debug' ); var inherit = require( '@stdlib/utils/inherit' ); @@ -135,7 +135,7 @@ function REPL( options ) { // Create an internal readline interface: debug( 'Creating readline interface...' ); - setNonEnumerableReadOnly( this, '_rli', readline.createInterface({ + setNonEnumerableReadOnly( this, '_rli', readline({ 'input': this._istream, 'output': this._ostream, 'terminal': opts.isTTY, @@ -177,7 +177,7 @@ function REPL( options ) { */ function onClose() { debug( 'Readline interface closed.' ); - debug( 'Exiting the REPL...' ); + debug( 'Exiting REPL...' ); self.emit( 'exit' ); } } @@ -271,7 +271,8 @@ setNonEnumerableReadOnly( REPL.prototype, 'close', function close() { // TODO: ensure REPL history is saved (flushed) to file before closing the REPL (see https://github.com/nodejs/node/blob/b21e7c7bcf23a2715951e4cd96180e4dbf1dcd4d/lib/repl.js#L805) - process.nextTick( onTick ); // TODO: replace with polyfill + // TODO: replace with polyfill + process.nextTick( onTick ); return this; @@ -281,7 +282,7 @@ setNonEnumerableReadOnly( REPL.prototype, 'close', function close() { * @private */ function onTick() { - debug( 'Closing the readline interface...' ); + debug( 'Closing readline interface...' ); self._rli.close(); } }); From 315f32c849da171c128b2dd25976e04332e2cbc5 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 02:20:03 -0700 Subject: [PATCH 027/142] Add support for printing top-level REPL help info --- .../repl/ctor/lib/create_new_context.js | 33 +++++++++++++++++-- .../@stdlib/repl/ctor/lib/drain.js | 2 +- .../@stdlib/repl/ctor/lib/help_text.js | 4 +-- .../@stdlib/repl/ctor/lib/main.js | 1 + 4 files changed, 34 insertions(+), 6 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js index c156375986d1..412838be6ad1 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js @@ -27,6 +27,7 @@ var setNonEnumerableReadOnly = require( '@stdlib/utils/define-nonenumerable-read var setNonEnumerableReadOnlyAccessor = require( '@stdlib/utils/define-nonenumerable-read-only-accessor' ); // eslint-disable-line id-length var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var createContext = require( './create_context.js' ); +var HELP_TEXT = require( './help_text.js' ); // VARIABLES // @@ -54,20 +55,30 @@ function createNewContext( repl ) { // Add commands requiring privileged access to internal instance variables: setNonEnumerableReadOnly( context, 'clear', onClear ); + setNonEnumerableReadOnly( context, 'help', onHelp ); setNonEnumerableReadOnly( context, 'load', onLoad ); setNonEnumerableReadOnly( context, 'quit', onQuit ); - // TODO: add `help` command // TODO: add `example` command + // TODO: add `namespace` command + // TODO: add `save` command - // TODO: add `recordStart` command - // TODO: add `recordStop` command + + // TODO: add `saveStart` command + + // TODO: add `saveStop` command + // TODO: add `citation` command + // TODO: add `license` command + // TODO: add `copyright` command + // TODO: add `contributors` command + // TODO: add `credits` command + // TODO: add `donate` command // Add an accessor for retrieving the result of the last successfully executed command: @@ -94,6 +105,22 @@ function createNewContext( repl ) { repl.clear(); } + /** + * Prints help text. + * + * @private + * @param {*} [alias] - variable alias or value + * @returns {void} + */ + function onHelp( alias ) { + if ( arguments.length === 0 ) { + repl._ostream.write( HELP_TEXT ); + return; + } + // TODO: add support for printing help text; first look through project namespace and then REPL-specific namespace + console.log( String( alias ) ); + } + /** * Loads and evaluates a JavaScript file line-by-line. * diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/drain.js b/lib/node_modules/@stdlib/repl/ctor/lib/drain.js index 55dce0f81cea..1a579369c08d 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/drain.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/drain.js @@ -108,7 +108,7 @@ function drain( repl ) { // TODO: evaluate and determine whether to print result opts = { 'displayErrors': false, - 'breakOnSigint': true // Note: applies only for Node.js versions >=6.3.0 + 'breakOnSigint': true // Note: applies for only Node.js versions >=6.3.0 }; try { if ( repl._sandbox ) { diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js b/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js index ac3fec7903f9..a3d857602c5f 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js @@ -35,8 +35,8 @@ var MSG = [ '', ' load( fpath ) Loads and evaluates a JavaScript file line-by-line.', ' save( fpath ) Saves previous commands to a specified file.', - ' recordStart( fpath ) Start saving commands to a specified file.', - ' recordStop( id ) Stop saving commands.', + ' saveStart( fpath ) Start saving commands to a specified file.', + ' saveStop( id ) Stop saving commands.', '', ' clear() Clears the REPL context.', ' quit() Exits the REPL.', diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index bbb08f9a8d21..60a7fcd8e0a0 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -52,6 +52,7 @@ var debug = logger( 'repl' ); /** * REPL constructor. * +* @constructor * @param {Options} options - constructor options * @param {string} [options.prompt='> '] - input prompt * @param {ReadableStream} [options.input=process.stdin] - input stream From 29979dec68e011a9e30f85c6fecfba72780dca81 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 02:54:35 -0700 Subject: [PATCH 028/142] Consolidate functions for creating the evaluation context --- .../@stdlib/repl/ctor/lib/clear.js | 4 +- .../@stdlib/repl/ctor/lib/create_context.js | 210 ++++++++++++++++-- .../repl/ctor/lib/create_new_context.js | 157 ------------- .../@stdlib/repl/ctor/lib/main.js | 4 +- 4 files changed, 194 insertions(+), 181 deletions(-) delete mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/clear.js b/lib/node_modules/@stdlib/repl/ctor/lib/clear.js index 9e7df95a1646..07fa8c7e677c 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/clear.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/clear.js @@ -23,7 +23,7 @@ // MODULES // var logger = require( 'debug' ); -var createNewContext = require( './create_new_context.js' ); +var createContext = require( './create_context.js' ); var displayPrompt = require( './display_prompt.js' ); @@ -54,7 +54,7 @@ function clear( repl ) { // When sandboxed, create a new execution context... if ( repl._sandbox ) { - repl._context = createNewContext( repl ); + repl._context = createContext( repl ); repl.emit( 'reset', repl._context ); } // Clear an output TTY stream of any previous commands and output: diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 107c8de050ed..ba66077a8dce 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -16,6 +16,8 @@ * limitations under the License. */ +/* eslint-disable no-underscore-dangle */ + 'use strict'; // MODULES // @@ -23,15 +25,23 @@ var Module = require( 'module' ); var vm = require( 'vm' ); var Console = require( 'console' ).Console; +var logger = require( 'debug' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var getGlobal = require( '@stdlib/utils/global' ); var objectKeys = require( '@stdlib/utils/keys' ); -var setNonEnumerable = require( '@stdlib/utils/define-nonenumerable-property' ); var defineProperty = require( '@stdlib/utils/define-property' ); +var setNonEnumerable = require( '@stdlib/utils/define-nonenumerable-property' ); +var setNonEnumerableReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var setNonEnumerableReadOnlyAccessor = require( '@stdlib/utils/define-nonenumerable-read-only-accessor' ); // eslint-disable-line id-length var createRequire = require( './create_require.js' ); +var HELP_TEXT = require( './help_text.js' ); // VARIABLES // +var debug = logger( 'repl:context' ); + // TODO: remove once we have stdlib pkg equivalents var GLOBALS = { 'Array': Array, @@ -63,7 +73,43 @@ var GLOBALS = { }; // Cache references to module methods (WARNING: we use private methods exposed on the `Module` object; thus, breakage is possible!): -var resolveLookupPaths = Module._resolveLookupPaths; // eslint-disable-line no-underscore-dangle +var resolveLookupPaths = Module._resolveLookupPaths; + + +// FUNCTIONS // + +/** +* Defines a configurable non-enumerable read-only property. +* +* @private +* @param {Object} obj - object on which to define the property +* @param {(string|symbol)} prop - property +* @param {*} value - value to assign +*/ +function setConfigurableReadOnly( obj, prop, value ) { + defineProperty( obj, prop, { + 'configurable': true, + 'enumerable': false, + 'writable': false, + 'value': value + }); +} + +/** +* Defines a configurable non-enumerable read-only accessor property. +* +* @private +* @param {Object} obj - object on which to define the property +* @param {(string|symbol)} prop - property +* @param {Function} accessor - accessor +*/ +function setConfigurableReadOnlyAccessor( obj, prop, accessor ) { // eslint-disable-line id-length + defineProperty( obj, prop, { + 'configurable': true, + 'enumerable': false, + 'get': accessor + }); +} // MAIN // @@ -72,44 +118,46 @@ var resolveLookupPaths = Module._resolveLookupPaths; // eslint-disable-line no-u * Creates a REPL context. * * @private -* @param {Options} options - context options -* @param {boolean} options.sandbox - boolean indicating whether to create a sandboxed context -* @param {WritableStream} options.output - output stream +* @param {REPL} repl - REPL instance * @returns {Object} REPL context */ -function createContext( options ) { +function createContext( repl ) { + var context; var Global; var keys; - var ctx; + var cmds; + var cmd; var i; + debug( 'Creating REPL execution context...' ); + Global = getGlobal(); - if ( options.sandbox ) { + if ( repl._sandbox ) { // Create a sandboxed context: - ctx = vm.createContext(); + context = vm.createContext(); // Assign globals from the current global context to the sandboxed context (note: shallow copy!)... keys = objectKeys( GLOBALS ); for ( i = 0; i < keys.length; i++ ) { - setNonEnumerable( ctx, keys[ i ], GLOBALS[ keys[ i ] ] ); + setNonEnumerable( context, keys[ i ], GLOBALS[ keys[ i ] ] ); } // Create a circular reference as in Node: - ctx.global = ctx; + context.global = context; // Create a new console interface: - setNonEnumerable( ctx, 'console', new Console( options.output ) ); + setNonEnumerable( context, 'console', new Console( repl._ostream ) ); // Create a new `module` object: - setNonEnumerable( ctx, 'module', new Module( '' ) ); + setNonEnumerable( context, 'module', new Module( '' ) ); // Create a new `require` function: - setNonEnumerable( ctx, 'require', createRequire( ctx.module ) ); + setNonEnumerable( context, 'require', createRequire( context.module ) ); } else { - ctx = Global; + context = Global; // Create a new `module` object: - defineProperty( ctx, 'module', { + defineProperty( context, 'module', { 'configurable': true, 'writable': false, 'enumerable': false, @@ -117,18 +165,140 @@ function createContext( options ) { }); // Create a new `require` function: - defineProperty( ctx, 'require', { + defineProperty( context, 'require', { 'configurable': true, 'writable': false, 'enumerable': false, - 'value': createRequire( ctx.module ) + 'value': createRequire( context.module ) }); } - ctx.module.paths = resolveLookupPaths( '', module, true ) || []; + context.module.paths = resolveLookupPaths( '', module, true ) || []; // TODO: lazy load project APIs (configurable, enumerable(?) accessors which overwrite themselves to become read-only properties; see https://github.com/nodejs/node/blob/0c1e93b9efadfc9fae74907a631908477c7d085e/lib/internal/modules/cjs/helpers.js#L102) - return ctx; + // Define a list of REPL-specific commands: + cmds = [ + // NOTE: keep in alphabetical order... + + // [ , , ] + [ 'ans', onAns, true ], + [ 'clear', onClear, false ], + [ 'help', onHelp, false ], + [ 'load', onLoad, false ], + [ 'quit', onQuit, false ] + ]; + + // TODO: add `example` command + + // TODO: add `namespace` command + + // TODO: add `save` command + + // TODO: add `saveStart` command + + // TODO: add `saveStop` command + + // TODO: add `citation` command + + // TODO: add `license` command + + // TODO: add `copyright` command + + // TODO: add `contributors` command + + // TODO: add `credits` command + + // TODO: add `donate` command + + // Add commands requiring privileged access to internal instance variables... + if ( repl._sandbox ) { + for ( i = 0; i < cmds.length; i++ ) { + cmd = cmds[ i ]; + if ( cmd[ 2 ] ) { + setNonEnumerableReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); + } else { + setNonEnumerableReadOnly( context, cmd[ 0 ], cmd[ 1 ] ); + } + } + } else { + for ( i = 0; i < cmds.length; i++ ) { + cmd = cmds[ i ]; + + // Avoid overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects... + if ( !hasOwnProp( context, cmd[ 0 ] ) ) { + if ( cmd[ 2 ] ) { + setConfigurableReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); // eslint-disable-line max-len + } else { + setConfigurableReadOnly( context, cmd[ 0 ], cmd[ 1 ] ); + } + } + } + } + return context; + + /** + * Returns the result of the last successfully executed command. + * + * @private + * @returns {*} result + */ + function onAns() { + return repl._ans; + } + + /** + * Clears a REPL's local context. + * + * @private + */ + function onClear() { + repl.clear(); + } + + /** + * Prints help text. + * + * @private + * @param {*} [alias] - variable alias or value + * @returns {void} + */ + function onHelp( alias ) { + if ( arguments.length === 0 ) { + repl._ostream.write( HELP_TEXT ); + return; + } + // TODO: add support for printing help text; first look through project namespace and then REPL-specific namespace + console.log( String( alias ) ); + } + + /** + * Loads and evaluates a JavaScript file line-by-line. + * + * @private + * @param {string} fpath - file path + * @returns {void} + */ + function onLoad( fpath ) { + var err; + if ( !isString( fpath ) ) { + err = new TypeError( 'invalid argument. Must provide a string. Value: `'+fpath+'`.' ); + debug( 'Error: %s', err.message ); + repl._ostream.write( 'Error: '+err.message+'\n' ); + return; + } + debug( 'Loading a file...' ); + repl.load( fpath ); + } + + /** + * Quits a REPL. + * + * @private + */ + function onQuit() { + debug( 'Quitting the REPL...' ); + repl.close(); + } } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js deleted file mode 100644 index 412838be6ad1..000000000000 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_new_context.js +++ /dev/null @@ -1,157 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2019 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* eslint-disable no-underscore-dangle */ - -'use strict'; - -// MODULES // - -var logger = require( 'debug' ); -var setNonEnumerableReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); -var setNonEnumerableReadOnlyAccessor = require( '@stdlib/utils/define-nonenumerable-read-only-accessor' ); // eslint-disable-line id-length -var isString = require( '@stdlib/assert/is-string' ).isPrimitive; -var createContext = require( './create_context.js' ); -var HELP_TEXT = require( './help_text.js' ); - - -// VARIABLES // - -var debug = logger( 'repl:context' ); - - -// MAIN // - -/** -* Creates a REPL execution context. -* -* @private -* @param {REPL} repl - REPL instance -* @returns {Object} REPL context -*/ -function createNewContext( repl ) { - var context; - - debug( 'Creating REPL execution context...' ); - context = createContext({ - 'sandbox': repl._sandbox, - 'output': repl._ostream - }); - - // Add commands requiring privileged access to internal instance variables: - setNonEnumerableReadOnly( context, 'clear', onClear ); - setNonEnumerableReadOnly( context, 'help', onHelp ); - setNonEnumerableReadOnly( context, 'load', onLoad ); - setNonEnumerableReadOnly( context, 'quit', onQuit ); - - // TODO: add `example` command - - // TODO: add `namespace` command - - // TODO: add `save` command - - // TODO: add `saveStart` command - - // TODO: add `saveStop` command - - // TODO: add `citation` command - - // TODO: add `license` command - - // TODO: add `copyright` command - - // TODO: add `contributors` command - - // TODO: add `credits` command - - // TODO: add `donate` command - - // Add an accessor for retrieving the result of the last successfully executed command: - setNonEnumerableReadOnlyAccessor( context, 'ans', onAns ); - - return context; - - /** - * Returns the result of the last successfully executed command. - * - * @private - * @returns {*} result - */ - function onAns() { - return repl._ans; - } - - /** - * Clears a REPL's local context. - * - * @private - */ - function onClear() { - repl.clear(); - } - - /** - * Prints help text. - * - * @private - * @param {*} [alias] - variable alias or value - * @returns {void} - */ - function onHelp( alias ) { - if ( arguments.length === 0 ) { - repl._ostream.write( HELP_TEXT ); - return; - } - // TODO: add support for printing help text; first look through project namespace and then REPL-specific namespace - console.log( String( alias ) ); - } - - /** - * Loads and evaluates a JavaScript file line-by-line. - * - * @private - * @param {string} fpath - file path - * @returns {void} - */ - function onLoad( fpath ) { - var err; - if ( !isString( fpath ) ) { - err = new TypeError( 'invalid argument. Must provide a string. Value: `'+fpath+'`.' ); - debug( 'Error: %s', err.message ); - repl._ostream.write( 'Error: '+err.message+'\n' ); - return; - } - debug( 'Loading a file...' ); - repl.load( fpath ); - } - - /** - * Quits a REPL. - * - * @private - */ - function onQuit() { - debug( 'Quitting the REPL...' ); - repl.close(); - } -} - - -// EXPORTS // - -module.exports = createNewContext; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index 60a7fcd8e0a0..85b7d2224b11 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -37,7 +37,7 @@ var fifo = require( '@stdlib/utils/fifo' ); var validate = require( './validate.js' ); var defaults = require( './defaults.js' ); var displayPrompt = require( './display_prompt.js' ); -var createNewContext = require( './create_new_context.js' ); +var createContext = require( './create_context.js' ); var processLine = require( './process_line.js' ); var clear = require( './clear.js' ); @@ -146,7 +146,7 @@ function REPL( options ) { this._rli.on( 'line', onLine ); // Create a REPL execution context: - setNonEnumerable( this, '_context', createNewContext( this ) ); + setNonEnumerable( this, '_context', createContext( this ) ); // Write a welcome message: this._ostream.write( opts.welcome ); From d4a71eb50f543a0558f156c851154499ad0bf891 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 03:04:53 -0700 Subject: [PATCH 029/142] Move utilities to separate files --- .../@stdlib/repl/ctor/lib/create_context.js | 77 ++----------------- .../define_configurable_read_only_accessor.js | 47 +++++++++++ .../define_configurable_read_only_property.js | 48 ++++++++++++ .../@stdlib/repl/ctor/lib/globals.js | 56 ++++++++++++++ 4 files changed, 157 insertions(+), 71 deletions(-) create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_accessor.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_property.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/globals.js diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index ba66077a8dce..796a084bfff7 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -34,84 +34,21 @@ var defineProperty = require( '@stdlib/utils/define-property' ); var setNonEnumerable = require( '@stdlib/utils/define-nonenumerable-property' ); var setNonEnumerableReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); var setNonEnumerableReadOnlyAccessor = require( '@stdlib/utils/define-nonenumerable-read-only-accessor' ); // eslint-disable-line id-length +var setConfigurableReadOnly = require( './define_configurable_read_only_property.js' ); +var setConfigurableReadOnlyAccessor = require( './define_configurable_read_only_accessor.js' ); // eslint-disable-line id-length var createRequire = require( './create_require.js' ); var HELP_TEXT = require( './help_text.js' ); +var GLOBALS = require( './globals.js' ); // VARIABLES // var debug = logger( 'repl:context' ); -// TODO: remove once we have stdlib pkg equivalents -var GLOBALS = { - 'Array': Array, - 'Boolean': Boolean, - 'Date': Date, - 'Function': Function, - 'Object': Object, - 'parseFloat': parseFloat, - 'parseInt': parseInt, - 'RegExp': RegExp, - 'String': String, - - // TODO: BigInt, DataView, Map, Set, Promise, Reflect(?), WeakMap, WeakSet, WebAssembly - - 'Error': Error, - 'EvalError': EvalError, - 'RangeError': RangeError, - 'ReferenceError': ReferenceError, - 'SyntaxError': SyntaxError, - 'TypeError': TypeError, - 'URIError': URIError, - - 'clearImmediate': clearImmediate, - 'clearInterval': clearInterval, - 'clearTimeout': clearTimeout, - 'setImmediate': setImmediate, - 'setInterval': setInterval, - 'setTimeout': setTimeout -}; - // Cache references to module methods (WARNING: we use private methods exposed on the `Module` object; thus, breakage is possible!): var resolveLookupPaths = Module._resolveLookupPaths; -// FUNCTIONS // - -/** -* Defines a configurable non-enumerable read-only property. -* -* @private -* @param {Object} obj - object on which to define the property -* @param {(string|symbol)} prop - property -* @param {*} value - value to assign -*/ -function setConfigurableReadOnly( obj, prop, value ) { - defineProperty( obj, prop, { - 'configurable': true, - 'enumerable': false, - 'writable': false, - 'value': value - }); -} - -/** -* Defines a configurable non-enumerable read-only accessor property. -* -* @private -* @param {Object} obj - object on which to define the property -* @param {(string|symbol)} prop - property -* @param {Function} accessor - accessor -*/ -function setConfigurableReadOnlyAccessor( obj, prop, accessor ) { // eslint-disable-line id-length - defineProperty( obj, prop, { - 'configurable': true, - 'enumerable': false, - 'get': accessor - }); -} - - // MAIN // /** @@ -142,10 +79,10 @@ function createContext( repl ) { setNonEnumerable( context, keys[ i ], GLOBALS[ keys[ i ] ] ); } - // Create a circular reference as in Node: + // Create a circular reference as in Node.js: context.global = context; - // Create a new console interface: + // Create a new `console` interface: setNonEnumerable( context, 'console', new Console( repl._ostream ) ); // Create a new `module` object: @@ -176,10 +113,8 @@ function createContext( repl ) { // TODO: lazy load project APIs (configurable, enumerable(?) accessors which overwrite themselves to become read-only properties; see https://github.com/nodejs/node/blob/0c1e93b9efadfc9fae74907a631908477c7d085e/lib/internal/modules/cjs/helpers.js#L102) - // Define a list of REPL-specific commands: + // Define a list of REPL-specific commands (NOTE: keep in alphabetical order): cmds = [ - // NOTE: keep in alphabetical order... - // [ , , ] [ 'ans', onAns, true ], [ 'clear', onClear, false ], diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_accessor.js b/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_accessor.js new file mode 100644 index 000000000000..c5c053d3cfff --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_accessor.js @@ -0,0 +1,47 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var defineProperty = require( '@stdlib/utils/define-property' ); + + +// MAIN // + +/** +* Defines a configurable non-enumerable read-only accessor. +* +* @private +* @param {Object} obj - object on which to define the accessor +* @param {(string|symbol)} prop - property +* @param {Function} accessor - accessor function +*/ +function setConfigurableReadOnlyAccessor( obj, prop, accessor ) { // eslint-disable-line id-length + defineProperty( obj, prop, { + 'configurable': true, + 'enumerable': false, + 'get': accessor + }); +} + + +// EXPORTS // + +module.exports = setConfigurableReadOnlyAccessor; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_property.js b/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_property.js new file mode 100644 index 000000000000..0de1a877861a --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_property.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var defineProperty = require( '@stdlib/utils/define-property' ); + + +// MAIN // + +/** +* Defines a configurable non-enumerable read-only property. +* +* @private +* @param {Object} obj - object on which to define the property +* @param {(string|symbol)} prop - property +* @param {*} value - value to assign +*/ +function setConfigurableReadOnly( obj, prop, value ) { + defineProperty( obj, prop, { + 'configurable': true, + 'enumerable': false, + 'writable': false, + 'value': value + }); +} + + +// EXPORTS // + +module.exports = setConfigurableReadOnly; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/globals.js b/lib/node_modules/@stdlib/repl/ctor/lib/globals.js new file mode 100644 index 000000000000..fbd0f8a66e10 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/globals.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +// TODO: remove once we have stdlib pkg equivalents +var GLOBALS = { + 'Array': Array, + 'Boolean': Boolean, + 'Date': Date, + 'Function': Function, + 'Object': Object, + 'parseFloat': parseFloat, + 'parseInt': parseInt, + 'RegExp': RegExp, + 'String': String, + + // TODO: BigInt, DataView, Map, Set, Promise, Reflect(?), WeakMap, WeakSet, WebAssembly + + 'Error': Error, + 'EvalError': EvalError, + 'RangeError': RangeError, + 'ReferenceError': ReferenceError, + 'SyntaxError': SyntaxError, + 'TypeError': TypeError, + 'URIError': URIError, + + 'clearImmediate': clearImmediate, + 'clearInterval': clearInterval, + 'clearTimeout': clearTimeout, + 'setImmediate': setImmediate, + 'setInterval': setInterval, + 'setTimeout': setTimeout +}; + + +// EXPORTS // + +module.exports = GLOBALS; From 5ffcf6c9f6254848e16015eacbaf816379f02e9f Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 03:42:57 -0700 Subject: [PATCH 030/142] Add index file --- .../@stdlib/repl/ctor/lib/create_context.js | 2 + .../@stdlib/repl/ctor/lib/help_text.js | 1 + .../@stdlib/repl/ctor/lib/index.js | 39 +++++++++++++++++++ 3 files changed, 42 insertions(+) create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/index.js diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 796a084bfff7..9d7c5c451f54 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -127,6 +127,8 @@ function createContext( repl ) { // TODO: add `namespace` command + // TODO: add `isKeyword` command + // TODO: add `save` command // TODO: add `saveStart` command diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js b/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js index a3d857602c5f..c35fc0b25158 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js @@ -32,6 +32,7 @@ var MSG = [ ' namespace() Lists namespace contents.', ' alias2pkg( alias ) Converts an alias to a stdlib package name.', ' pkg2alias( pkg ) Converts a stdlib package name to an alias.', + ' isKeyword( value ) Asserts whether a value is a reserved keyword/alias.', '', ' load( fpath ) Loads and evaluates a JavaScript file line-by-line.', ' save( fpath ) Saves previous commands to a specified file.', diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/index.js b/lib/node_modules/@stdlib/repl/ctor/lib/index.js new file mode 100644 index 000000000000..e0e338005374 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/index.js @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* REPL environment. +* +* @module @stdlib/repl/ctor +* +* @example +* var REPL = require( '@stdlib/repl/ctor' ); +* +* // TODO +*/ + +// MODULES // + +var REPL = require( './main.js' ); + + +// EXPORTS // + +module.exports = REPL; From e6098ec3f63478076736e3f8a36f8dd91f969a17 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 03:43:31 -0700 Subject: [PATCH 031/142] Update require path --- lib/node_modules/@stdlib/repl/ctor/examples/index.js | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/examples/index.js b/lib/node_modules/@stdlib/repl/ctor/examples/index.js index 73b6dfa6c853..f0edb037e1e6 100644 --- a/lib/node_modules/@stdlib/repl/ctor/examples/index.js +++ b/lib/node_modules/@stdlib/repl/ctor/examples/index.js @@ -18,13 +18,12 @@ 'use strict'; -var REPL = require( './../lib/main.js' ); - -function onExit() { - console.log( 'REPL closed.' ); -} +var REPL = require( './../lib' ); // Create a new REPL: var repl = new REPL(); - repl.on( 'exit', onExit ); + +function onExit() { + console.log( 'REPL closed.' ); +} From c5c77cd5c1f6548f5744e79ac1bd6dfd57d01243 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 03:45:42 -0700 Subject: [PATCH 032/142] Update example --- .../@stdlib/repl/ctor/examples/index.js | 14 +++++++++++--- 1 file changed, 11 insertions(+), 3 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/examples/index.js b/lib/node_modules/@stdlib/repl/ctor/examples/index.js index f0edb037e1e6..77f6319f7514 100644 --- a/lib/node_modules/@stdlib/repl/ctor/examples/index.js +++ b/lib/node_modules/@stdlib/repl/ctor/examples/index.js @@ -20,10 +20,18 @@ var REPL = require( './../lib' ); -// Create a new REPL: -var repl = new REPL(); -repl.on( 'exit', onExit ); +var repl; function onExit() { console.log( 'REPL closed.' ); } + +function onTimeout() { + repl.close(); +} + +// Create a new REPL: +repl = new REPL(); +repl.on( 'exit', onExit ); + +setTimeout( onTimeout, 5000 ); From 2497ce9fbd96f0eb3035d9b50bb7cc2f9ea2c691 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 03:52:48 -0700 Subject: [PATCH 033/142] Add `package.json` --- .../@stdlib/repl/ctor/package.json | 72 +++++++++++++++++++ 1 file changed, 72 insertions(+) create mode 100644 lib/node_modules/@stdlib/repl/ctor/package.json diff --git a/lib/node_modules/@stdlib/repl/ctor/package.json b/lib/node_modules/@stdlib/repl/ctor/package.json new file mode 100644 index 000000000000..0f9c446c0100 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/repl/ctor", + "version": "0.0.0", + "description": "REPL environment.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "bin": { + "stdlib-repl-server": "./bin/cli" + }, + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "bin": "./bin", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "repl", + "read-eval-print-loop", + "eval", + "evaluate", + "interact", + "interactive", + "console", + "terminal", + "shell", + "server" + ], + "__stdlib__": { + "envs": { + "browser": false + } + } +} From 00302536949f9613db0af5a6af228c8619f82517 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 13:11:38 -0700 Subject: [PATCH 034/142] Add benchmarks --- .../@stdlib/repl/ctor/benchmark/benchmark.js | 93 +++++++++++++++++++ 1 file changed, 93 insertions(+) create mode 100644 lib/node_modules/@stdlib/repl/ctor/benchmark/benchmark.js diff --git a/lib/node_modules/@stdlib/repl/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/repl/ctor/benchmark/benchmark.js new file mode 100644 index 000000000000..6ff484294a64 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/benchmark/benchmark.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var inspectSinkStream = require( '@stdlib/streams/node/inspect-sink' ); +var randu = require( '@stdlib/random/streams/randu' ); +var noop = require( '@stdlib/utils/noop' ); +var pkg = require( './../package.json' ).name; +var REPL = require( './../lib' ); + + +// MAIN // + +bench( pkg+'::new', function benchmark( b ) { + var sopts; + var opts; + var r; + var i; + + opts = { + 'output': inspectSinkStream( noop ) + }; + sopts = { + 'iter': 1 + }; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + opts.input = randu( sopts ); // Note: this is slow, but should not be rate-limiting + r = new REPL( opts ); + if ( typeof r !== 'object' ) { + b.fail( 'should return an object' ); + } + r.close(); + } + b.toc(); + if ( !( r instanceof REPL ) ) { + b.fail( 'should return an instance' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::no_new', function benchmark( b ) { + var sopts; + var repl; + var opts; + var r; + var i; + + repl = REPL; + opts = { + 'output': inspectSinkStream( noop ) + }; + sopts = { + 'iter': 1 + }; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + opts.input = randu( sopts ); // Note: this is slow, but should not be rate-limiting + r = repl( opts ); + if ( typeof r !== 'object' ) { + b.fail( 'should return an object' ); + } + r.close(); + } + b.toc(); + if ( !( r instanceof REPL ) ) { + b.fail( 'should return an instance' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); From afcb37d7b189bf766b77141f6ad43613dc5e7fbd Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 16:56:07 -0700 Subject: [PATCH 035/142] Update examples --- lib/node_modules/@stdlib/datasets/month-names-en/README.md | 5 ++--- .../@stdlib/datasets/month-names-en/examples/index.js | 5 ++--- 2 files changed, 4 insertions(+), 6 deletions(-) diff --git a/lib/node_modules/@stdlib/datasets/month-names-en/README.md b/lib/node_modules/@stdlib/datasets/month-names-en/README.md index 364f19e68e10..7fe33b61816d 100644 --- a/lib/node_modules/@stdlib/datasets/month-names-en/README.md +++ b/lib/node_modules/@stdlib/datasets/month-names-en/README.md @@ -67,8 +67,7 @@ var list = months(); ```javascript -var floor = require( '@stdlib/math/base/special/floor' ); -var randu = require( '@stdlib/random/base/randu' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var months = require( '@stdlib/datasets/month-names-en' ); var list; @@ -81,7 +80,7 @@ len = list.length; // Select random months from the list... for ( i = 0; i < 100; i++ ) { - idx = floor( randu()*len ); + idx = discreteUniform( 0, len ); console.log( list[ idx ] ); } ``` diff --git a/lib/node_modules/@stdlib/datasets/month-names-en/examples/index.js b/lib/node_modules/@stdlib/datasets/month-names-en/examples/index.js index 0c8bb753f3e5..1daad0627761 100644 --- a/lib/node_modules/@stdlib/datasets/month-names-en/examples/index.js +++ b/lib/node_modules/@stdlib/datasets/month-names-en/examples/index.js @@ -18,8 +18,7 @@ 'use strict'; -var floor = require( '@stdlib/math/base/special/floor' ); -var randu = require( '@stdlib/random/base/randu' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); var months = require( './../lib' ); var list; @@ -32,6 +31,6 @@ len = list.length; // Select random months from the list... for ( i = 0; i < 100; i++ ) { - idx = floor( randu()*len ); + idx = discreteUniform( 0, len ); console.log( list[ idx ] ); } From bf9caf101a2b70db19857ac6fd4a41f377c4d688 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 17:03:44 -0700 Subject: [PATCH 036/142] Add utility to list namespace aliases --- .../@stdlib/namespace/aliases/LICENSE | 356 ++++ .../@stdlib/namespace/aliases/README.md | 135 ++ .../namespace/aliases/benchmark/benchmark.js | 48 + .../@stdlib/namespace/aliases/bin/cli | 70 + .../@stdlib/namespace/aliases/data/data.json | 1 + .../@stdlib/namespace/aliases/data/data.txt | 1883 +++++++++++++++++ .../namespace/aliases/datapackage.json | 36 + .../@stdlib/namespace/aliases/docs/repl.txt | 17 + .../namespace/aliases/docs/types/index.d.ts | 35 + .../namespace/aliases/docs/types/test.ts | 32 + .../@stdlib/namespace/aliases/docs/usage.txt | 8 + .../namespace/aliases/etc/cli_opts.json | 15 + .../namespace/aliases/examples/index.js | 36 + .../@stdlib/namespace/aliases/lib/index.js | 40 + .../@stdlib/namespace/aliases/lib/main.js | 44 + .../@stdlib/namespace/aliases/package.json | 66 + .../namespace/aliases/scripts/build.js | 74 + .../namespace/aliases/test/test.cli.js | 167 ++ .../@stdlib/namespace/aliases/test/test.js | 48 + 19 files changed, 3111 insertions(+) create mode 100644 lib/node_modules/@stdlib/namespace/aliases/LICENSE create mode 100644 lib/node_modules/@stdlib/namespace/aliases/README.md create mode 100644 lib/node_modules/@stdlib/namespace/aliases/benchmark/benchmark.js create mode 100755 lib/node_modules/@stdlib/namespace/aliases/bin/cli create mode 100644 lib/node_modules/@stdlib/namespace/aliases/data/data.json create mode 100644 lib/node_modules/@stdlib/namespace/aliases/data/data.txt create mode 100644 lib/node_modules/@stdlib/namespace/aliases/datapackage.json create mode 100644 lib/node_modules/@stdlib/namespace/aliases/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/namespace/aliases/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/namespace/aliases/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/namespace/aliases/docs/usage.txt create mode 100644 lib/node_modules/@stdlib/namespace/aliases/etc/cli_opts.json create mode 100644 lib/node_modules/@stdlib/namespace/aliases/examples/index.js create mode 100644 lib/node_modules/@stdlib/namespace/aliases/lib/index.js create mode 100644 lib/node_modules/@stdlib/namespace/aliases/lib/main.js create mode 100644 lib/node_modules/@stdlib/namespace/aliases/package.json create mode 100644 lib/node_modules/@stdlib/namespace/aliases/scripts/build.js create mode 100644 lib/node_modules/@stdlib/namespace/aliases/test/test.cli.js create mode 100644 lib/node_modules/@stdlib/namespace/aliases/test/test.js diff --git a/lib/node_modules/@stdlib/namespace/aliases/LICENSE b/lib/node_modules/@stdlib/namespace/aliases/LICENSE new file mode 100644 index 000000000000..dc6d53e33997 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/LICENSE @@ -0,0 +1,356 @@ +The use of the database is licensed under an Open Data Commons Public Domain +Dedication & License 1.0 (PDDL 1.0), while the database contents are licensed +under Creative Commons Zero v1.0 Universal (CC0 1.0). 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If the rights waived or granted under applicable law in the relevant jurisdiction includes additional rights not waived or granted under this Document, these additional rights are included in this Document in order to meet the intent of this Document. diff --git a/lib/node_modules/@stdlib/namespace/aliases/README.md b/lib/node_modules/@stdlib/namespace/aliases/README.md new file mode 100644 index 000000000000..511a253d8a5b --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/README.md @@ -0,0 +1,135 @@ + + +# Aliases + +> A list of standard library aliases. + +
+ +## Usage + +```javascript +var aliases = require( '@stdlib/namespace/aliases' ); +``` + +#### aliases() + +Returns a list of standard library aliases. + +```javascript +var list = aliases(); +// returns [...] +``` + +
+ + + +
+ + + +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); + +var list; +var len; +var idx; +var i; + +list = aliases(); +len = list.length; + +// Select random aliases from the list... +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len ); + console.log( list[ idx ] ); +} + +``` + +
+ + + +* * * + +
+ +## CLI + +
+ +### Usage + +```text +Usage: stdlib-aliases [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. +``` + +
+ + + +
+ +### Examples + +```bash +$ stdlib-aliases +``` + +
+ + + +
+ + + + + +## License + +The data files (databases) are licensed under an [Open Data Commons Public Domain Dedication & License 1.0][pddl-1.0] and their contents are licensed under [Creative Commons Zero v1.0 Universal][cc0]. The software is licensed under [Apache License, Version 2.0][apache-license]. + + + +
+ +[pddl-1.0]: http://opendatacommons.org/licenses/pddl/1.0/ + +[cc0]: https://creativecommons.org/publicdomain/zero/1.0 + +[apache-license]: https://www.apache.org/licenses/LICENSE-2.0 + +
+ + diff --git a/lib/node_modules/@stdlib/namespace/aliases/benchmark/benchmark.js b/lib/node_modules/@stdlib/namespace/aliases/benchmark/benchmark.js new file mode 100644 index 000000000000..42c5e7751ae5 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/benchmark/benchmark.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isStringArray = require( '@stdlib/assert/is-string-array' ).primitives; +var pkg = require( './../package.json' ).name; +var aliases = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = aliases(); + if ( typeof v !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( !isStringArray( v ) ) { + b.fail( 'should return an array of strings' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/namespace/aliases/bin/cli b/lib/node_modules/@stdlib/namespace/aliases/bin/cli new file mode 100755 index 000000000000..b1e852fc5cf7 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/bin/cli @@ -0,0 +1,70 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var fs = require( 'fs' ); +var resolve = require( 'path' ).resolve; +var readFileSync = require( '@stdlib/fs/read-file' ).sync; +var stdout = require( '@stdlib/streams/node/stdout' ); +var CLI = require( '@stdlib/tools/cli' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var fpath; + var cli; + + // Create a command-line interface: + cli = new CLI({ + 'pkg': require( './../package.json' ), + 'options': require( './../etc/cli_opts.json' ), + 'help': readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }) + }); + + // Resolve the data file path: + fpath = resolve( __dirname, '..', 'data', 'data.txt' ); + + // Print the data to stdout: + fs.createReadStream( fpath ) + .pipe( stdout ) + .on( 'close', onClose ); + + /** + * Exits the CLI. + * + * @private + */ + function onClose() { + cli.exit( 0 ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.json b/lib/node_modules/@stdlib/namespace/aliases/data/data.json new file mode 100644 index 000000000000..3cbce1e13b0e --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.json @@ -0,0 +1 @@ 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+LIU_POSITIVE_OPINION_WORDS_EN +LN_HALF +LN_PI +LN_SQRT_TWO_PI +LN_TWO_PI +LN2 +LN10 +LOG2E +LOG10E +logspace +lowercase +lowercaseKeys +lowess +lpad +ltrim +MALE_FIRST_NAMES_EN +mapFun +mapFunAsync +mapKeys +mapKeysAsync +mapValues +mapValuesAsync +MAX_ARRAY_LENGTH +MAX_TYPED_ARRAY_LENGTH +memoize +merge +MILLISECONDS_IN_DAY +MILLISECONDS_IN_HOUR +MILLISECONDS_IN_MINUTE +MILLISECONDS_IN_SECOND +MILLISECONDS_IN_WEEK +MINARD_NAPOLEONS_MARCH +MINUTES_IN_DAY +MINUTES_IN_HOUR +MINUTES_IN_WEEK +minutesInMonth +minutesInYear +MOBY_DICK +MONTH_NAMES_EN +MONTHS_IN_YEAR +moveProperty +namedtypedtuple +nativeClass +ndarray +ndarrayCastingModes +ndarrayDataTypes +ndarrayIndexModes +ndarrayMemoized +ndarrayMinDataType +ndarrayNextDataType +ndarrayOrders +ndarrayPromotionRules +ndarraySafeCasts +ndarraySameKindCasts +NIGHTINGALES_ROSE +NINF +NODE_VERSION +none +noneBy +noneByAsync +noneByRight +noneByRightAsync +nonEnumerableProperties +nonEnumerablePropertiesIn +nonEnumerablePropertyNames 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+RE_DIRNAME_WINDOWS +RE_EOL +RE_EXTENDED_LENGTH_PATH +RE_EXTNAME +RE_EXTNAME_POSIX +RE_EXTNAME_WINDOWS +RE_FILENAME +RE_FILENAME_POSIX +RE_FILENAME_WINDOWS +RE_FUNCTION_NAME +RE_NATIVE_FUNCTION +RE_REGEXP +RE_UNC_PATH +RE_UTF16_SURROGATE_PAIR +RE_UTF16_UNPAIRED_SURROGATE +RE_WHITESPACE +readDir +readFile +readFileList +readJSON +readWASM +real +realmax +realmin +reduce +reduceAsync +reduceRight +reduceRightAsync +reFromString +reim +removeFirst +removeLast +removePunctuation +removeUTF8BOM +removeWords +rename +reorderArguments +repeat +replace +rescape +resolveParentPath +reverseArguments +reverseString +reviveBasePRNG +reviveBuffer +reviveComplex +reviveComplex64 +reviveComplex128 +reviveError +reviveTypedArray +rpad +rtrim +safeintmax +safeintmin +sample +SAVOY_STOPWORDS_FIN +SAVOY_STOPWORDS_FR +SAVOY_STOPWORDS_GER +SAVOY_STOPWORDS_IT +SAVOY_STOPWORDS_POR +SAVOY_STOPWORDS_SP +SAVOY_STOPWORDS_SWE +SECONDS_IN_DAY +SECONDS_IN_HOUR +SECONDS_IN_MINUTE +SECONDS_IN_WEEK +secondsInMonth +secondsInYear +setNonEnumerableProperty +setNonEnumerableReadOnly +setNonEnumerableReadOnlyAccessor +setNonEnumerableReadWriteAccessor +setNonEnumerableWriteOnlyAccessor +setReadOnly +setReadOnlyAccessor +setReadWriteAccessor +setWriteOnlyAccessor +SharedArrayBuffer +shift +shuffle +sizeOf +some +someBy +someByAsync +someByRight +someByRightAsync +SOTU +SPACHE_REVISED +SPAM_ASSASSIN +SparklineBase +sparsearray2iterator +sparsearray2iteratorRight +splitStream +SQRT_EPS +SQRT_HALF +SQRT_HALF_PI +SQRT_PHI +SQRT_PI +SQRT_THREE +SQRT_TWO +SQRT_TWO_PI +Stack +startcase +startsWith +STOPWORDS_EN +stridedarray2iterator +stridedArrayStream +string2buffer +sub2ind +SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK +SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK +Symbol +tabulate +tabulateBy +tabulateByAsync +tic +timeit +tmpdir +toc +tokenize +transformStream +trim +trycatch +trycatchAsync +tryFunction +tryRequire +trythen +trythenAsync +ttest +ttest2 +TWO_PI +typedarray +typedarray2json +typedarrayComplexCtors +typedarrayComplexDataTypes +typedarrayCtors +typedarrayDataTypes +typedarraypool +typemax +typemin +typeOf +UINT8_MAX +UINT8_NUM_BYTES +Uint8Array +Uint8ClampedArray +UINT16_MAX +UINT16_NUM_BYTES +Uint16Array +UINT32_MAX +UINT32_NUM_BYTES +Uint32Array +umask +uncapitalize +uncapitalizeKeys +uncurry +uncurryRight +UNICODE_MAX +UNICODE_MAX_BMP +UnicodeColumnChartSparkline +UnicodeLineChartSparkline +UnicodeSparkline +UnicodeTristateChartSparkline +UnicodeUpDownChartSparkline +UnicodeWinLossChartSparkline +unlink +unshift +until +untilAsync +untilEach +untilEachRight +unzip +uppercase +uppercaseKeys +US_STATES_ABBR +US_STATES_CAPITALS +US_STATES_CAPITALS_NAMES +US_STATES_NAMES +US_STATES_NAMES_CAPITALS +utf16ToUTF8Array +vartest +waterfall +whileAsync +whileEach +whileEachRight +whilst +writableProperties +writablePropertiesIn +writablePropertyNames +writablePropertyNamesIn +writablePropertySymbols +writablePropertySymbolsIn +writeFile +zip +ztest +ztest2 \ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/datapackage.json b/lib/node_modules/@stdlib/namespace/aliases/datapackage.json new file mode 100644 index 000000000000..60c924142cf9 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/datapackage.json @@ -0,0 +1,36 @@ +{ + "name": "stdlib-aliases", + "version": "", + "title": "Standard Library Aliases", + "description": "A list of standard library aliases.", + "resources": [ + { + "name": "stdlib-aliases-json", + "title": "Standard Library Aliases", + "description": "A list of standard library aliases.", + "format": "json", + "mediatype": "application/json", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.json" + }, + { + "name": "stdlib-aliases-txt", + "title": "Standard Library Aliases", + "description": "A list of standard library aliases.", + "format": "text", + "mediatype": "plain/text", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.txt" + } + ], + "sources": [], + "keywords": [ + "list", + "stdlib", + "namespace", + "aliases" + ], + "license": "PDDL-1.0 AND CC0-1.0" +} diff --git a/lib/node_modules/@stdlib/namespace/aliases/docs/repl.txt b/lib/node_modules/@stdlib/namespace/aliases/docs/repl.txt new file mode 100644 index 000000000000..9822a8e42450 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/docs/repl.txt @@ -0,0 +1,17 @@ + +{{alias}}() + Returns a list of standard library aliases. + + Returns + ------- + out: Array + List of aliases. + + Examples + -------- + > var o = {{alias}}() + [...] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/namespace/aliases/docs/types/index.d.ts b/lib/node_modules/@stdlib/namespace/aliases/docs/types/index.d.ts new file mode 100644 index 000000000000..7e9fde35186f --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/docs/types/index.d.ts @@ -0,0 +1,35 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Returns a list of standard library aliases. +* +* @returns list of aliases +* +* @example +* var list = aliases(); +* // returns [...] +*/ +declare function aliases(): Array; + + +// EXPORTS // + +export = aliases; diff --git a/lib/node_modules/@stdlib/namespace/aliases/docs/types/test.ts b/lib/node_modules/@stdlib/namespace/aliases/docs/types/test.ts new file mode 100644 index 000000000000..d39061c04ee9 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/docs/types/test.ts @@ -0,0 +1,32 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import aliases = require( './index' ); + + +// TESTS // + +// The function returns an array of strings... +{ + aliases(); // $ExpectType string[] +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + aliases( 'beep' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/namespace/aliases/docs/usage.txt b/lib/node_modules/@stdlib/namespace/aliases/docs/usage.txt new file mode 100644 index 000000000000..3dc63abb2069 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/docs/usage.txt @@ -0,0 +1,8 @@ + +Usage: stdlib-aliases [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. + diff --git a/lib/node_modules/@stdlib/namespace/aliases/etc/cli_opts.json b/lib/node_modules/@stdlib/namespace/aliases/etc/cli_opts.json new file mode 100644 index 000000000000..92119c456962 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/etc/cli_opts.json @@ -0,0 +1,15 @@ +{ + "string": [], + "boolean": [ + "help", + "version" + ], + "alias": { + "help": [ + "h" + ], + "version": [ + "V" + ] + } +} diff --git a/lib/node_modules/@stdlib/namespace/aliases/examples/index.js b/lib/node_modules/@stdlib/namespace/aliases/examples/index.js new file mode 100644 index 000000000000..443c27edad47 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( './../lib' ); + +var list; +var len; +var idx; +var i; + +list = aliases(); +len = list.length; + +// Select random aliases from the list... +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len ); + console.log( list[ idx ] ); +} diff --git a/lib/node_modules/@stdlib/namespace/aliases/lib/index.js b/lib/node_modules/@stdlib/namespace/aliases/lib/index.js new file mode 100644 index 000000000000..d97266ba6e22 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Standard library aliases. +* +* @module @stdlib/namespace/aliases +* +* @example +* var aliases = require( '@stdlib/namespace/aliases' ); +* +* var list = aliases(); +* // returns [...] +*/ + +// MODULES // + +var aliases = require( './main.js' ); + + +// EXPORTS // + +module.exports = aliases; diff --git a/lib/node_modules/@stdlib/namespace/aliases/lib/main.js b/lib/node_modules/@stdlib/namespace/aliases/lib/main.js new file mode 100644 index 000000000000..0d67f790b4a1 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/lib/main.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var ALIASES = require( './../data/data.json' ); + + +// MAIN // + +/** +* Returns a list of standard library aliases. +* +* @returns {StringArray} list of aliases +* +* @example +* var list = aliases(); +* // returns [...] +*/ +function aliases() { + return ALIASES.slice(); +} + + +// EXPORTS // + +module.exports = aliases; diff --git a/lib/node_modules/@stdlib/namespace/aliases/package.json b/lib/node_modules/@stdlib/namespace/aliases/package.json new file mode 100644 index 000000000000..615e4ff38a1e --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/namespace/aliases", + "version": "0.0.0", + "description": "Standard library aliases.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "bin": { + "stdlib-aliases": "./bin/cli" + }, + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "bin": "./bin", + "data": "./data", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "standard", + "library", + "lib", + "aliases", + "alias", + "namespace", + "dataset", + "data" + ] +} diff --git a/lib/node_modules/@stdlib/namespace/aliases/scripts/build.js b/lib/node_modules/@stdlib/namespace/aliases/scripts/build.js new file mode 100644 index 000000000000..3bbb1eb081da --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/scripts/build.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var logger = require( 'debug' ); +var writeFile = require( '@stdlib/fs/write-file' ).sync; +var namespace = require( '@stdlib/namespace' ); + + +// VARIABLES // + +var debug = logger( 'namespace:aliases:build' ); + +// Output file paths: +var OUTPUT_JSON = resolve( __dirname, '..', 'data', 'data.json' ); +var OUTPUT_TEXT = resolve( __dirname, '..', 'data', 'data.txt' ); + + +// FUNCTIONS // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var fopts; + var list; + var ns; + var i; + + debug( 'Extracting list of namespace aliases...' ); + ns = namespace(); + list = []; + for ( i = 0; i < ns.length; i++ ) { + list.push( ns[ i ].alias ); + } + + debug( 'Writing list of namespace aliases to JSON file...' ); + fopts = { + 'encoding': 'utf8' + }; + writeFile( OUTPUT_JSON, JSON.stringify( list ), fopts ); + + debug( 'Writing list of namespace aliases to text file...' ); + fopts = { + 'encoding': 'utf8' + }; + writeFile( OUTPUT_TEXT, list.join( '\n' ), fopts ); +} + + +// MAIN // + +main(); diff --git a/lib/node_modules/@stdlib/namespace/aliases/test/test.cli.js b/lib/node_modules/@stdlib/namespace/aliases/test/test.cli.js new file mode 100644 index 000000000000..152515d239e7 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/test/test.cli.js @@ -0,0 +1,167 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var exec = require( 'child_process' ).exec; +var tape = require( 'tape' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); +var readFileSync = require( '@stdlib/fs/read-file' ).sync; + + +// VARIABLES // + +var fpath = resolve( __dirname, '..', 'bin', 'cli' ); +var opts = { + 'skip': IS_BROWSER || IS_WINDOWS +}; + + +// FIXTURES // + +var PKG_VERSION = require( './../package.json' ).version; + + +// TESTS // + +tape( 'command-line interface', function test( t ) { + t.ok( true, __filename ); + t.end(); +}); + +tape( 'when invoked with a `--help` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '--help' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-h` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '-h' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `--version` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '--version' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-V` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '-V' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'the command-line interface prints the list of aliases', opts, function test( t ) { + var expected; + var cmd; + + cmd = [ + process.execPath, + fpath + ]; + + expected = readFileSync( resolve( __dirname, '..', 'data', 'data.txt' ) ); + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + stdout = stdout.toString(); + expected = expected.toString(); + t.strictEqual( stdout, expected, 'prints expected values' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + } + t.end(); + } +}); diff --git a/lib/node_modules/@stdlib/namespace/aliases/test/test.js b/lib/node_modules/@stdlib/namespace/aliases/test/test.js new file mode 100644 index 000000000000..7dda3a515ea1 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/aliases/test/test.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isStringArray = require( '@stdlib/assert/is-string-array' ).primitives; +var aliases = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof aliases, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a list of aliases', function test( t ) { + var o1; + var o2; + + o1 = aliases(); + t.strictEqual( isStringArray( o1 ), true, 'returns an array of strings' ); + + o2 = aliases(); + t.strictEqual( isStringArray( o2 ), true, 'returns an array of strings' ); + t.notEqual( o1, o2, 'returns new reference' ); + + t.end(); +}); From 9195a5ee97e1f9a27692ba1129aa8bcb3438e0b3 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 17:07:32 -0700 Subject: [PATCH 037/142] Add task to update list of namespace aliases --- tools/make/lib/docs/repl.mk | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/tools/make/lib/docs/repl.mk b/tools/make/lib/docs/repl.mk index 6e65650e7c06..d0e070aa0307 100644 --- a/tools/make/lib/docs/repl.mk +++ b/tools/make/lib/docs/repl.mk @@ -24,6 +24,9 @@ REPL_HELP ?= $(SRC_DIR)/@stdlib/repl/help/scripts/build.js # Define the path to the executable for aggregating REPL examples: REPL_EXAMPLES ?= $(SRC_DIR)/@stdlib/repl/code-blocks/scripts/build.js +# Define the path to the executable for aggregating REPL aliases: +REPL_ALIASES ?= $(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js + # TARGETS # @@ -31,7 +34,7 @@ REPL_EXAMPLES ?= $(SRC_DIR)/@stdlib/repl/code-blocks/scripts/build.js # # This target generates REPL documentation. -repl-docs: repl-help repl-examples +repl-docs: repl-help repl-examples repl-aliases .PHONY: repl-docs @@ -54,3 +57,13 @@ repl-examples: $(NODE_MODULES) $(REPL_EXAMPLES) $(QUIET) $(NODE) $(REPL_EXAMPLES) .PHONY: repl-examples + + +# Aggregate REPL aliases. +# +# This target aggregates REPL aliases. + +repl-aliases: $(NODE_MODULES) $(REPL_ALIASES) + $(QUIET) $(NODE) $(REPL_ALIASES) + +.PHONY: repl-aliases From 0c18983e3d155bd1b36226d514fb5239ae937b44 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 17:08:27 -0700 Subject: [PATCH 038/142] Update database --- lib/node_modules/@stdlib/namespace/aliases/data/data.json | 2 +- lib/node_modules/@stdlib/namespace/aliases/data/data.txt | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.json b/lib/node_modules/@stdlib/namespace/aliases/data/data.json index 3cbce1e13b0e..9d4d76a01815 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.json +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index e9c43cc05daa..17a744b54812 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1,5 +1,6 @@ AFINN_96 AFINN_111 +aliases allocUnsafe anova1 ANSCOMBES_QUARTET From 648ac8486e2d20fec1c90de56ea66b8e254ff78d Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 17:08:47 -0700 Subject: [PATCH 039/142] Update namespace --- .../@stdlib/namespace/lib/namespace/a.js | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/a.js b/lib/node_modules/@stdlib/namespace/lib/namespace/a.js index 31ada5d119b7..529a777dc4d3 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/a.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/a.js @@ -46,6 +46,18 @@ ns.push({ ] }); +ns.push({ + 'alias': 'aliases', + 'path': '@stdlib/namespace/aliases', + 'value': require( '@stdlib/namespace/aliases' ), + 'type': 'Function', + 'related': [ + '@stdlib/namespace/alias2pkg', + '@stdlib/namespace/alias2related', + '@stdlib/namespace/pkg2alias' + ] +}); + ns.push({ 'alias': 'allocUnsafe', 'path': '@stdlib/buffer/alloc-unsafe', From 934611d748b010fc4c37210c7813c4e31d3daf0f Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 17:09:14 -0700 Subject: [PATCH 040/142] Update namespace --- lib/node_modules/@stdlib/repl/code-blocks/lib/db.js | 1 + lib/node_modules/@stdlib/repl/help/lib/db.js | 1 + 2 files changed, 2 insertions(+) diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index 13450b5aee80..8b2f1d560e68 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -26,6 +26,7 @@ var db = { "AFINN_96": "list = AFINN_96()\n", "AFINN_111": "list = AFINN_111()\n", + "aliases": "o = aliases()\n", "allocUnsafe": "buf = allocUnsafe( 100 )\n", "anova1": "x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nf = [\n'control', 'treatA', 'treatB', 'treatC', 'control',\n'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n];\nout = anova1( x, f )\n", "ANSCOMBES_QUARTET": "d = ANSCOMBES_QUARTET()\n", diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index 48e5e0eb6731..cf6f268a64bb 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -26,6 +26,7 @@ var db = { "AFINN_96": "\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n", "AFINN_111": "\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n", + "aliases": "\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n", "allocUnsafe": "\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n", "anova1": "\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n", "ANSCOMBES_QUARTET": "\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n", From c965fcb0c5fdfdd195f2734dd3b9099f33086681 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 18:34:58 -0700 Subject: [PATCH 041/142] Fix example --- lib/node_modules/@stdlib/namespace/aliases/README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/lib/node_modules/@stdlib/namespace/aliases/README.md b/lib/node_modules/@stdlib/namespace/aliases/README.md index 511a253d8a5b..5083396e5e06 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/README.md +++ b/lib/node_modules/@stdlib/namespace/aliases/README.md @@ -68,7 +68,6 @@ for ( i = 0; i < 100; i++ ) { idx = discreteUniform( 0, len ); console.log( list[ idx ] ); } - ``` From c4ee75853d5c3687e5139d775a122ddf4971c9a4 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 19:05:54 -0700 Subject: [PATCH 042/142] Add utility to map an alias to a package name --- .../@stdlib/namespace/alias2pkg/README.md | 174 ++ .../alias2pkg/benchmark/benchmark.js | 52 + .../@stdlib/namespace/alias2pkg/bin/cli | 64 + .../@stdlib/namespace/alias2pkg/data/data.csv | 1884 +++++++++++++++++ .../namespace/alias2pkg/data/data.json | 1 + .../@stdlib/namespace/alias2pkg/docs/repl.txt | 22 + .../namespace/alias2pkg/docs/types/index.d.ts | 36 + .../namespace/alias2pkg/docs/types/test.ts | 44 + .../namespace/alias2pkg/docs/usage.txt | 8 + .../namespace/alias2pkg/etc/cli_opts.json | 15 + .../namespace/alias2pkg/examples/index.js | 38 + .../@stdlib/namespace/alias2pkg/lib/index.js | 40 + .../@stdlib/namespace/alias2pkg/lib/main.js | 56 + .../@stdlib/namespace/alias2pkg/package.json | 67 + .../namespace/alias2pkg/scripts/build.js | 82 + .../namespace/alias2pkg/test/test.cli.js | 181 ++ .../@stdlib/namespace/alias2pkg/test/test.js | 93 + 17 files changed, 2857 insertions(+) create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/README.md create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/benchmark/benchmark.js create mode 100755 lib/node_modules/@stdlib/namespace/alias2pkg/bin/cli create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/docs/usage.txt create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/etc/cli_opts.json create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/examples/index.js create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/lib/index.js create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/lib/main.js create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/package.json create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/scripts/build.js create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/test/test.cli.js create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/test/test.js diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/README.md b/lib/node_modules/@stdlib/namespace/alias2pkg/README.md new file mode 100644 index 000000000000..65218b23552e --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/README.md @@ -0,0 +1,174 @@ + + +# alias2pkg + +> Return the package name associated with a specified alias. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +``` + +#### alias2pkg( alias ) + +Returns the package name associated with a specified `alias`. + +```javascript +var v = alias2pkg( 'base.sin' ); +// returns '@stdlib/math/base/special/sin' +``` + +If provided an unrecognized `alias`, the function returns `null`. + +```javascript +var v = alias2pkg( 'unrecognized_alias_beep_boop_bop_bip' ); +// returns null +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); + +var list; +var len; +var idx; +var v; +var i; + +list = aliases(); +len = list.length; + +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len ); + v = list[ idx ]; + console.log( 'alias: %s. pkg: %s.', v, alias2pkg( v ) ); +} +``` + +
+ + + + + +* * * + +
+ +## CLI + + + +
+ +### Usage + +```text +Usage: stdlib-alias2pkg [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```bash +$ stdlib-alias2pkg 'base.sin' +@stdlib/math/base/special/sin +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/benchmark/benchmark.js b/lib/node_modules/@stdlib/namespace/alias2pkg/benchmark/benchmark.js new file mode 100644 index 000000000000..894dfc31c382 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/benchmark/benchmark.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var aliases = require( '@stdlib/namespace/aliases' ); +var pkg = require( './../package.json' ).name; +var alias2pkg = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var v; + var i; + + values = aliases(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = alias2pkg( values[ i%values.length ] ); + if ( typeof v !== 'string' ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( v ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/bin/cli b/lib/node_modules/@stdlib/namespace/alias2pkg/bin/cli new file mode 100755 index 000000000000..a767303b3536 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/bin/cli @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var readFileSync = require( '@stdlib/fs/read-file' ).sync; +var CLI = require( '@stdlib/tools/cli' ); +var alias2pkg = require( './../lib' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var args; + var cli; + var out; + + // Create a command-line interface: + cli = new CLI({ + 'pkg': require( './../package.json' ), + 'options': require( './../etc/cli_opts.json' ), + 'help': readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }) + }); + + // Get any provided command-line arguments: + args = cli.args(); + + // Resolve a provided alias to a package name... + out = alias2pkg( args[ 0 ] ); + if ( out ) { + console.log( out ); // eslint-disable-line no-console + } else { + cli.exit( 1 ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv new file mode 100644 index 000000000000..35e40320735e --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -0,0 +1,1884 @@ +AFINN_96,"@stdlib/datasets/afinn-96" +AFINN_111,"@stdlib/datasets/afinn-111" +aliases,"@stdlib/namespace/aliases" +allocUnsafe,"@stdlib/buffer/alloc-unsafe" +anova1,"@stdlib/stats/anova1" +ANSCOMBES_QUARTET,"@stdlib/datasets/anscombes-quartet" +any,"@stdlib/utils/any" +anyBy,"@stdlib/utils/any-by" +anyByAsync,"@stdlib/utils/async/any-by" +anyByRight,"@stdlib/utils/any-by-right" +anyByRightAsync,"@stdlib/utils/async/any-by-right" +APERY,"@stdlib/constants/math/float64-apery" +append,"@stdlib/utils/append" +ARCH,"@stdlib/os/arch" +argumentFunction,"@stdlib/utils/argument-function" +ARGV,"@stdlib/process/argv" +array,"@stdlib/ndarray/array" +array2buffer,"@stdlib/buffer/from-array" +array2iterator,"@stdlib/array/to-iterator" +array2iteratorRight,"@stdlib/array/to-iterator-right" +ArrayBuffer,"@stdlib/array/buffer" +arraybuffer2buffer,"@stdlib/buffer/from-arraybuffer" +arrayCtors,"@stdlib/array/ctors" +arrayDataType,"@stdlib/array/dtype" +arrayDataTypes,"@stdlib/array/dtypes" +arrayMinDataType,"@stdlib/array/min-dtype" +arrayNextDataType,"@stdlib/array/next-dtype" +arrayPromotionRules,"@stdlib/array/promotion-rules" +arraySafeCasts,"@stdlib/array/safe-casts" +arraySameKindCasts,"@stdlib/array/same-kind-casts" +arrayShape,"@stdlib/array/shape" +arrayStream,"@stdlib/streams/node/from-array" +arrayview2iterator,"@stdlib/array/to-view-iterator" +arrayview2iteratorRight,"@stdlib/array/to-view-iterator-right" +AsyncIteratorSymbol,"@stdlib/symbol/async-iterator" +bartlettTest,"@stdlib/stats/bartlett-test" +base.abs,"@stdlib/math/base/special/abs" +base.abs2,"@stdlib/math/base/special/abs2" +base.absdiff,"@stdlib/math/base/utils/absolute-difference" +base.absInt32,"@stdlib/math/base/special/int32-abs" +base.acos,"@stdlib/math/base/special/acos" +base.acosh,"@stdlib/math/base/special/acosh" +base.acoth,"@stdlib/math/base/special/acoth" +base.acovercos,"@stdlib/math/base/special/acovercos" +base.acoversin,"@stdlib/math/base/special/acoversin" +base.ahavercos,"@stdlib/math/base/special/ahavercos" +base.ahaversin,"@stdlib/math/base/special/ahaversin" +base.asin,"@stdlib/math/base/special/asin" +base.asinh,"@stdlib/math/base/special/asinh" +base.atan,"@stdlib/math/base/special/atan" +base.atan2,"@stdlib/math/base/special/atan2" +base.atanh,"@stdlib/math/base/special/atanh" +base.avercos,"@stdlib/math/base/special/avercos" +base.aversin,"@stdlib/math/base/special/aversin" +base.bernoulli,"@stdlib/math/base/special/bernoulli" +base.besselj0,"@stdlib/math/base/special/besselj0" +base.besselj1,"@stdlib/math/base/special/besselj1" +base.bessely0,"@stdlib/math/base/special/bessely0" +base.bessely1,"@stdlib/math/base/special/bessely1" +base.beta,"@stdlib/math/base/special/beta" +base.betainc,"@stdlib/math/base/special/betainc" +base.betaincinv,"@stdlib/math/base/special/betaincinv" +base.betaln,"@stdlib/math/base/special/betaln" +base.binet,"@stdlib/math/base/special/binet" +base.binomcoef,"@stdlib/math/base/special/binomcoef" +base.binomcoefln,"@stdlib/math/base/special/binomcoefln" +base.boxcox,"@stdlib/math/base/special/boxcox" +base.boxcox1p,"@stdlib/math/base/special/boxcox1p" +base.boxcox1pinv,"@stdlib/math/base/special/boxcox1pinv" +base.boxcoxinv,"@stdlib/math/base/special/boxcoxinv" +base.cabs,"@stdlib/math/base/complex/abs" +base.cabs2,"@stdlib/math/base/complex/abs2" +base.cadd,"@stdlib/math/base/complex/add" +base.cbrt,"@stdlib/math/base/special/cbrt" +base.cceil,"@stdlib/math/base/complex/ceil" +base.cceiln,"@stdlib/math/base/complex/ceiln" +base.ccis,"@stdlib/math/base/complex/cis" +base.cdiv,"@stdlib/math/base/complex/divide" +base.ceil,"@stdlib/math/base/special/ceil" +base.ceil2,"@stdlib/math/base/special/ceil2" +base.ceil10,"@stdlib/math/base/special/ceil10" +base.ceilb,"@stdlib/math/base/special/ceilb" +base.ceiln,"@stdlib/math/base/special/ceiln" +base.ceilsd,"@stdlib/math/base/special/ceilsd" +base.cexp,"@stdlib/math/base/complex/exp" +base.cflipsign,"@stdlib/math/base/complex/flipsign" +base.cfloor,"@stdlib/math/base/complex/floor" +base.cfloorn,"@stdlib/math/base/complex/floorn" +base.cinv,"@stdlib/math/base/complex/inv" +base.clamp,"@stdlib/math/base/special/clamp" +base.cmul,"@stdlib/math/base/complex/multiply" +base.cneg,"@stdlib/math/base/complex/negate" +base.continuedFraction,"@stdlib/math/base/tools/continued-fraction" +base.copysign,"@stdlib/math/base/special/copysign" +base.cos,"@stdlib/math/base/special/cos" +base.cosh,"@stdlib/math/base/special/cosh" +base.cosm1,"@stdlib/math/base/special/cosm1" +base.cospi,"@stdlib/math/base/special/cospi" +base.covercos,"@stdlib/math/base/special/covercos" +base.coversin,"@stdlib/math/base/special/coversin" +base.cphase,"@stdlib/math/base/complex/phase" +base.cpolar,"@stdlib/math/base/complex/polar" +base.cround,"@stdlib/math/base/complex/round" +base.croundn,"@stdlib/math/base/complex/roundn" +base.csignum,"@stdlib/math/base/complex/signum" +base.csub,"@stdlib/math/base/complex/subtract" +base.dasum,"@stdlib/blas/base/dasum" +base.daxpy,"@stdlib/blas/base/daxpy" +base.dcopy,"@stdlib/blas/base/dcopy" +base.deg2rad,"@stdlib/math/base/special/deg2rad" +base.digamma,"@stdlib/math/base/special/digamma" +base.diracDelta,"@stdlib/math/base/special/dirac-delta" +base.dists.arcsine.Arcsine,"@stdlib/stats/base/dists/arcsine/ctor" +base.dists.arcsine.cdf,"@stdlib/stats/base/dists/arcsine/cdf" +base.dists.arcsine.entropy,"@stdlib/stats/base/dists/arcsine/entropy" +base.dists.arcsine.kurtosis,"@stdlib/stats/base/dists/arcsine/kurtosis" +base.dists.arcsine.logcdf,"@stdlib/stats/base/dists/arcsine/logcdf" +base.dists.arcsine.logpdf,"@stdlib/stats/base/dists/arcsine/logpdf" +base.dists.arcsine.mean,"@stdlib/stats/base/dists/arcsine/mean" +base.dists.arcsine.median,"@stdlib/stats/base/dists/arcsine/median" +base.dists.arcsine.mode,"@stdlib/stats/base/dists/arcsine/mode" +base.dists.arcsine.pdf,"@stdlib/stats/base/dists/arcsine/pdf" +base.dists.arcsine.quantile,"@stdlib/stats/base/dists/arcsine/quantile" +base.dists.arcsine.skewness,"@stdlib/stats/base/dists/arcsine/skewness" +base.dists.arcsine.stdev,"@stdlib/stats/base/dists/arcsine/stdev" +base.dists.arcsine.variance,"@stdlib/stats/base/dists/arcsine/variance" +base.dists.bernoulli.Bernoulli,"@stdlib/stats/base/dists/bernoulli/ctor" +base.dists.bernoulli.cdf,"@stdlib/stats/base/dists/bernoulli/cdf" +base.dists.bernoulli.entropy,"@stdlib/stats/base/dists/bernoulli/entropy" +base.dists.bernoulli.kurtosis,"@stdlib/stats/base/dists/bernoulli/kurtosis" +base.dists.bernoulli.mean,"@stdlib/stats/base/dists/bernoulli/mean" +base.dists.bernoulli.median,"@stdlib/stats/base/dists/bernoulli/median" +base.dists.bernoulli.mgf,"@stdlib/stats/base/dists/bernoulli/mgf" +base.dists.bernoulli.mode,"@stdlib/stats/base/dists/bernoulli/mode" +base.dists.bernoulli.pmf,"@stdlib/stats/base/dists/bernoulli/pmf" +base.dists.bernoulli.quantile,"@stdlib/stats/base/dists/bernoulli/quantile" +base.dists.bernoulli.skewness,"@stdlib/stats/base/dists/bernoulli/skewness" +base.dists.bernoulli.stdev,"@stdlib/stats/base/dists/bernoulli/stdev" +base.dists.bernoulli.variance,"@stdlib/stats/base/dists/bernoulli/variance" +base.dists.beta.Beta,"@stdlib/stats/base/dists/beta/ctor" +base.dists.beta.cdf,"@stdlib/stats/base/dists/beta/cdf" +base.dists.beta.entropy,"@stdlib/stats/base/dists/beta/entropy" +base.dists.beta.kurtosis,"@stdlib/stats/base/dists/beta/kurtosis" +base.dists.beta.logcdf,"@stdlib/stats/base/dists/beta/logcdf" +base.dists.beta.logpdf,"@stdlib/stats/base/dists/beta/logpdf" +base.dists.beta.mean,"@stdlib/stats/base/dists/beta/mean" +base.dists.beta.median,"@stdlib/stats/base/dists/beta/median" +base.dists.beta.mgf,"@stdlib/stats/base/dists/beta/mgf" +base.dists.beta.mode,"@stdlib/stats/base/dists/beta/mode" +base.dists.beta.pdf,"@stdlib/stats/base/dists/beta/pdf" +base.dists.beta.quantile,"@stdlib/stats/base/dists/beta/quantile" +base.dists.beta.skewness,"@stdlib/stats/base/dists/beta/skewness" +base.dists.beta.stdev,"@stdlib/stats/base/dists/beta/stdev" +base.dists.beta.variance,"@stdlib/stats/base/dists/beta/variance" +base.dists.betaprime.BetaPrime,"@stdlib/stats/base/dists/betaprime/ctor" +base.dists.betaprime.cdf,"@stdlib/stats/base/dists/betaprime/cdf" +base.dists.betaprime.kurtosis,"@stdlib/stats/base/dists/betaprime/kurtosis" +base.dists.betaprime.logcdf,"@stdlib/stats/base/dists/betaprime/logcdf" +base.dists.betaprime.logpdf,"@stdlib/stats/base/dists/betaprime/logpdf" +base.dists.betaprime.mean,"@stdlib/stats/base/dists/betaprime/mean" +base.dists.betaprime.mode,"@stdlib/stats/base/dists/betaprime/mode" +base.dists.betaprime.pdf,"@stdlib/stats/base/dists/betaprime/pdf" +base.dists.betaprime.quantile,"@stdlib/stats/base/dists/betaprime/quantile" +base.dists.betaprime.skewness,"@stdlib/stats/base/dists/betaprime/skewness" +base.dists.betaprime.stdev,"@stdlib/stats/base/dists/betaprime/stdev" +base.dists.betaprime.variance,"@stdlib/stats/base/dists/betaprime/variance" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/docs/repl.txt b/lib/node_modules/@stdlib/namespace/alias2pkg/docs/repl.txt new file mode 100644 index 000000000000..635a89856808 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/docs/repl.txt @@ -0,0 +1,22 @@ + +{{alias}}( alias ) + Returns the package name associated with a provided alias. + + Parameters + ---------- + alias: string + Alias. + + Returns + ------- + out: string|null + Package name. + + Examples + -------- + > var v = {{alias}}( '{{alias:@stdlib/math/base/special/sin}}' ) + '@stdlib/math/base/special/sin' + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/docs/types/index.d.ts b/lib/node_modules/@stdlib/namespace/alias2pkg/docs/types/index.d.ts new file mode 100644 index 000000000000..d15290806ca3 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/docs/types/index.d.ts @@ -0,0 +1,36 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Returns a package name associated with a specified alias. +* +* @param alias - alias +* @returns package name +* +* @example +* var v = alias2pkg( 'base.sin' ); +* // returns '@stdlib/math/base/special/sin' +*/ +declare function alias2pkg( alias: string ): string | null; + + +// EXPORTS // + +export = alias2pkg; diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/docs/types/test.ts b/lib/node_modules/@stdlib/namespace/alias2pkg/docs/types/test.ts new file mode 100644 index 000000000000..a3148c28cc16 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import alias2pkg = require( './index' ); + + +// TESTS // + +// The function returns a string or null... +{ + alias2pkg( 'base.sin' ); // $ExpectType string | null +} + +// The compiler throws an error if the function is not provided a string... +{ + alias2pkg( 5 ); // $ExpectError + alias2pkg( true ); // $ExpectError + alias2pkg( false ); // $ExpectError + alias2pkg( null ); // $ExpectError + alias2pkg( undefined ); // $ExpectError + alias2pkg( [] ); // $ExpectError + alias2pkg( {} ); // $ExpectError + alias2pkg( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + alias2pkg( 'base.sin', 'beep' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/docs/usage.txt b/lib/node_modules/@stdlib/namespace/alias2pkg/docs/usage.txt new file mode 100644 index 000000000000..cfb5b141ec97 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/docs/usage.txt @@ -0,0 +1,8 @@ + +Usage: stdlib-alias2pkg [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. + diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/etc/cli_opts.json b/lib/node_modules/@stdlib/namespace/alias2pkg/etc/cli_opts.json new file mode 100644 index 000000000000..92119c456962 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/etc/cli_opts.json @@ -0,0 +1,15 @@ +{ + "string": [], + "boolean": [ + "help", + "version" + ], + "alias": { + "help": [ + "h" + ], + "version": [ + "V" + ] + } +} diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/examples/index.js b/lib/node_modules/@stdlib/namespace/alias2pkg/examples/index.js new file mode 100644 index 000000000000..bab54d1757d9 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2pkg = require( './../lib' ); + +var list; +var len; +var idx; +var v; +var i; + +list = aliases(); +len = list.length; + +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len ); + v = list[ idx ]; + console.log( 'alias: %s. pkg: %s.', v, alias2pkg( v ) ); +} diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/lib/index.js b/lib/node_modules/@stdlib/namespace/alias2pkg/lib/index.js new file mode 100644 index 000000000000..df97f6503048 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the package name associated with a specified alias. +* +* @module @stdlib/namespace/alias2pkg +* +* @example +* var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +* +* var v = alias2pkg( 'base.sin' ); +* // returns '@stdlib/math/base/special/sin' +*/ + +// MODULES // + +var alias2pkg = require( './main.js' ); + + +// EXPORTS // + +module.exports = alias2pkg; diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/lib/main.js b/lib/node_modules/@stdlib/namespace/alias2pkg/lib/main.js new file mode 100644 index 000000000000..32774f28106b --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/lib/main.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var ALIAS_TO_PKG = require( './../data/data.json' ); + + +// MAIN // + +/** +* Returns the package name associated with a specified alias. +* +* @param {string} alias - alias +* @throws {TypeError} must provide a string +* @returns {(string|null)} package name +* +* @example +* var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +* +* var v = alias2pkg( 'base.sin' ); +* // returns '@stdlib/math/base/special/sin' +*/ +function alias2pkg( alias ) { + if ( !isString( alias ) ) { + throw new TypeError( 'invalid argument. Must provide a string. Value: `' + alias + '`.' ); + } + if ( hasOwnProp( ALIAS_TO_PKG, alias ) ) { + return ALIAS_TO_PKG[ alias ]; + } + return null; +} + + +// EXPORTS // + +module.exports = alias2pkg; diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/package.json b/lib/node_modules/@stdlib/namespace/alias2pkg/package.json new file mode 100644 index 000000000000..4d3c9b474b52 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/namespace/alias2pkg", + "version": "0.0.0", + "description": "Return the package name associated with a specified alias.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "bin": { + "stdlib-alias2pkg": "./bin/cli" + }, + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "bin": "./bin", + "data": "./data", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "standard", + "library", + "lib", + "aliases", + "alias", + "namespace", + "package", + "name", + "pkg" + ] +} diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/scripts/build.js b/lib/node_modules/@stdlib/namespace/alias2pkg/scripts/build.js new file mode 100644 index 000000000000..c9653f168c9c --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/scripts/build.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var logger = require( 'debug' ); +var writeFile = require( '@stdlib/fs/write-file' ).sync; +var namespace = require( '@stdlib/namespace' ); +var objectKeys = require( '@stdlib/utils/keys' ); + + +// VARIABLES // + +var debug = logger( 'namespace:alias2pkg:build' ); + +// Output file paths: +var OUTPUT_JSON = resolve( __dirname, '..', 'data', 'data.json' ); +var OUTPUT_CSV = resolve( __dirname, '..', 'data', 'data.csv' ); + + +// FUNCTIONS // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var fopts; + var keys; + var json; + var csv; + var ns; + var i; + + debug( 'Extracting namespace aliases and package names...' ); + ns = namespace(); + json = {}; + for ( i = 0; i < ns.length; i++ ) { + json[ ns[i].alias ] = ns[ i ].path; + } + + debug( 'Writing to JSON file...' ); + fopts = { + 'encoding': 'utf8' + }; + writeFile( OUTPUT_JSON, JSON.stringify( json ), fopts ); + + debug( 'Writing to CSV file...' ); + fopts = { + 'encoding': 'utf8' + }; + keys = objectKeys( json ); + csv = ''; + for ( i = 0; i < keys.length; i++ ) { + csv += keys[ i ] + ',"' + json[ keys[i] ] + '"\n'; // Note: ensures trailing newline + } + writeFile( OUTPUT_CSV, csv, fopts ); +} + + +// MAIN // + +main(); diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/test/test.cli.js b/lib/node_modules/@stdlib/namespace/alias2pkg/test/test.cli.js new file mode 100644 index 000000000000..dec567371a76 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/test/test.cli.js @@ -0,0 +1,181 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var exec = require( 'child_process' ).exec; +var tape = require( 'tape' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); +var readFileSync = require( '@stdlib/fs/read-file' ).sync; + + +// VARIABLES // + +var fpath = resolve( __dirname, '..', 'bin', 'cli' ); +var opts = { + 'skip': IS_BROWSER || IS_WINDOWS +}; + + +// FIXTURES // + +var PKG_VERSION = require( './../package.json' ).version; + + +// TESTS // + +tape( 'command-line interface', function test( t ) { + t.ok( true, __filename ); + t.end(); +}); + +tape( 'when invoked with a `--help` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '--help' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-h` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '-h' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `--version` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '--version' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-V` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '-V' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'the command-line interface prints a package name', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + 'base.sin' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '@stdlib/math/base/special/sin\n', 'prints expected value' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + } + t.end(); + } +}); + +tape( 'if unable to resolve a package name, the command-line interface sets a non-zero exit code', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + 'fjaldfjadljfeoejreandfljasdfjadsfjs' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.pass( error.message ); + t.strictEqual( error.code, 1, 'expected exit code' ); + } + t.strictEqual( stdout.toString(), '', 'does not print to` stdout`' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + t.end(); + } +}); diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/test/test.js b/lib/node_modules/@stdlib/namespace/alias2pkg/test/test.js new file mode 100644 index 000000000000..fe16e00e63f9 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/test/test.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var DATA = require( './../data/data.json' ); +var alias2pkg = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof alias2pkg, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a string', function test( t ) { + var values; + var i; + + values = [ + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + alias2pkg( value ); + }; + } +}); + +tape( 'the function returns a package name', function test( t ) { + var expected; + var actual; + var list; + var i; + + list = aliases(); + for ( i = 0; i < list.length; i++ ) { + expected = DATA[ list[i] ]; + actual = alias2pkg( list[i] ); + t.strictEqual( typeof actual, 'string', 'returns a string' ); + t.strictEqual( actual, expected, 'returns expected value for '+list[i] ); + } + t.end(); +}); + +tape( 'the function returns `null` if provided an unrecognized alias', function test( t ) { + var values; + var i; + + values = [ + 'adfkaljdfdsafs', + 'adklfadjflajdslfjalsdf', + 'adflkajdlkfjasdlkfjsadlkfjlasdjflsdjfla' + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( alias2pkg( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); From a68872fc2b02666c4f423e9edf00e15cf4ab5d5d Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 19:11:10 -0700 Subject: [PATCH 043/142] Patch alias mangling behavior and add TODOs --- .../_tools/repl-txt/rules/doctest/lib/main.js | 42 +++++++++++++++---- 1 file changed, 33 insertions(+), 9 deletions(-) diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/doctest/lib/main.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/doctest/lib/main.js index 22d09b5f2e79..f8e70e2ecb6c 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/doctest/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/doctest/lib/main.js @@ -24,14 +24,14 @@ var vm = require( 'vm' ); var dirname = require( 'path' ).dirname; var replace = require( '@stdlib/string/replace' ); var namespace = require( '@stdlib/namespace' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var compareValues = require( '@stdlib/_tools/doctest/compare-values' ); // VARIABLES // -var RE_OUTSIDE_ALIAS = /{{alias:([\s\S]+?)}}/g; +var RE_EXTERNAL_ALIAS = /{{alias:([\s\S]+?)}}/g; var RE_ASSIGNMENT = /(?:var|let|const)? ?([a-zA-Z0-9]*) ?=/; -var RE_DOT = /\.([a-z])/gi; var NAMESPACE = namespace(); @@ -51,7 +51,6 @@ function pkg2alias( pkg ) { for ( i = 0; i < NAMESPACE.length; i++ ) { if ( pkg === NAMESPACE[ i ].path ) { alias = NAMESPACE[ i ].alias; - alias = replace( alias, RE_DOT, '$1' ); return alias; } } @@ -90,6 +89,8 @@ function main( context ) { var b; var i; + // FIXME: clean-up this logic + if ( context.meta.filepath ) { expected = []; actual = []; @@ -100,15 +101,27 @@ function main( context ) { 'require': require }; pkgName = pkg2alias( pkg ) || 'ALIAS'; - scope[ pkgName ] = require( pkg ); // eslint-disable-line stdlib/no-dynamic-require + + // TODO: move unflattening logic to utility function + pkgName = pkgName.split( '.' ); + for ( i = 0; i < pkgName.length; i++ ) { + if ( i < pkgName.length-1 ) { + if ( !hasOwnProp( scope, pkgName[i] ) ) { + scope[ pkgName[i] ] = {}; + } + } else { + scope[ pkgName[i] ] = require( pkg ); // eslint-disable-line stdlib/no-dynamic-require + } + } + // TODO: process external aliases *BEFORE* creating the context (and also, what is going on here, given that the return value is ignored?) vm.createContext( scope ); examples = section.examples; for ( i = 0; i < examples.length; i++ ) { current = examples[ i ]; code = current.code; - code = replace( code, '{{alias}}', pkgName ); - code = replace( code, RE_OUTSIDE_ALIAS, replaceAliases ); + code = replace( code, '{{alias}}', pkgName.join( '.' ) ); + code = replace( code, RE_EXTERNAL_ALIAS, replaceAliases ); try { out = vm.runInContext( code, scope ); if ( current.output ) { @@ -137,7 +150,7 @@ function main( context ) { } /** - * Replaces aliases to other packages in REPL example code, while registering the respective packages in the `scope` of the generated function. + * Replaces aliases to other packages in REPL example code and registers the respective packages in the runtime context. * * @private * @param {string} match - full match @@ -146,8 +159,19 @@ function main( context ) { */ function replaceAliases( match, pkg ) { var alias = pkg2alias( pkg ); - scope[ alias ] = require( pkg ); // eslint-disable-line stdlib/no-dynamic-require - return alias; + + // TODO: move unflattening logic to utility function + alias = alias.split( '.' ); + for ( i = 0; i < alias.length; i++ ) { + if ( i < alias.length-1 ) { + if ( !hasOwnProp( scope, alias[i] ) ) { + scope[ alias[i] ] = {}; + } + } else { + scope[ alias[i] ] = require( pkg ); // eslint-disable-line stdlib/no-dynamic-require + } + } + return alias.join( '.' ); } } From cda14c1fbd5c3b7f2e38e50d397a64744872bcd8 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 19:16:18 -0700 Subject: [PATCH 044/142] Update recipe to generate mapping between aliases and pkg names --- tools/make/lib/docs/repl.mk | 33 +++++++++++++++++++++++---------- 1 file changed, 23 insertions(+), 10 deletions(-) diff --git a/tools/make/lib/docs/repl.mk b/tools/make/lib/docs/repl.mk index d0e070aa0307..ef608dba9734 100644 --- a/tools/make/lib/docs/repl.mk +++ b/tools/make/lib/docs/repl.mk @@ -19,13 +19,16 @@ # VARIABLES # # Define the path to the executable for generating REPL help docs: -REPL_HELP ?= $(SRC_DIR)/@stdlib/repl/help/scripts/build.js +REPL_BUILD_HELP ?= $(SRC_DIR)/@stdlib/repl/help/scripts/build.js # Define the path to the executable for aggregating REPL examples: -REPL_EXAMPLES ?= $(SRC_DIR)/@stdlib/repl/code-blocks/scripts/build.js +REPL_BUILD_EXAMPLES ?= $(SRC_DIR)/@stdlib/repl/code-blocks/scripts/build.js # Define the path to the executable for aggregating REPL aliases: -REPL_ALIASES ?= $(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js +REPL_BUILD_ALIASES ?= $(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js + +# Define the path to the executable for mapping REPL aliases to package names: +REPL_BUILD_ALIAS2PKG ?= $(SRC_DIR)/@stdlib/namespace/alias2pkg/scripts/build.js # TARGETS # @@ -34,7 +37,7 @@ REPL_ALIASES ?= $(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js # # This target generates REPL documentation. -repl-docs: repl-help repl-examples repl-aliases +repl-docs: repl-help repl-examples repl-aliases repl-alias2pkg .PHONY: repl-docs @@ -43,8 +46,8 @@ repl-docs: repl-help repl-examples repl-aliases # # This target generates REPL help documentation. -repl-help: $(NODE_MODULES) $(REPL_HELP) - $(QUIET) $(NODE) $(REPL_HELP) +repl-help: $(NODE_MODULES) $(REPL_BUILD_HELP) + $(QUIET) $(NODE) $(REPL_BUILD_HELP) .PHONY: repl-help @@ -53,8 +56,8 @@ repl-help: $(NODE_MODULES) $(REPL_HELP) # # This target aggregates REPL examples. -repl-examples: $(NODE_MODULES) $(REPL_EXAMPLES) - $(QUIET) $(NODE) $(REPL_EXAMPLES) +repl-examples: $(NODE_MODULES) $(REPL_BUILD_EXAMPLES) + $(QUIET) $(NODE) $(REPL_BUILD_EXAMPLES) .PHONY: repl-examples @@ -63,7 +66,17 @@ repl-examples: $(NODE_MODULES) $(REPL_EXAMPLES) # # This target aggregates REPL aliases. -repl-aliases: $(NODE_MODULES) $(REPL_ALIASES) - $(QUIET) $(NODE) $(REPL_ALIASES) +repl-aliases: $(NODE_MODULES) $(REPL_BUILD_ALIASES) + $(QUIET) $(NODE) $(REPL_BUILD_ALIASES) .PHONY: repl-aliases + + +# Build the mapping between REPL aliases and package names. +# +# This target rebuilds the REPL database. + +repl-alias2pkg: $(NODE_MODULES) $(REPL_BUILD_ALIAS2PKG) + $(QUIET) $(NODE) $(REPL_BUILD_ALIAS2PKG) + +.PHONY: repl-alias2pkg From f8ae62b19798863913264e5fece597d649fc2323 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 19:18:12 -0700 Subject: [PATCH 045/142] Update namespace --- .../@stdlib/namespace/alias2pkg/data/data.csv | 1 + .../@stdlib/namespace/alias2pkg/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.txt | 1 + .../@stdlib/namespace/lib/namespace/a.js | 12 ++++++++++++ lib/node_modules/@stdlib/repl/code-blocks/lib/db.js | 1 + .../@stdlib/repl/ctor/lib/create_context.js | 4 +--- lib/node_modules/@stdlib/repl/ctor/lib/drain.js | 6 +++--- lib/node_modules/@stdlib/repl/ctor/lib/help_text.js | 2 +- .../@stdlib/repl/ctor/lib/process_line.js | 5 ++++- lib/node_modules/@stdlib/repl/help/lib/db.js | 3 ++- 11 files changed, 28 insertions(+), 11 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index 35e40320735e..fcbec6faa200 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1,5 +1,6 @@ AFINN_96,"@stdlib/datasets/afinn-96" AFINN_111,"@stdlib/datasets/afinn-111" +alias2pkg,"@stdlib/namespace/alias2pkg" aliases,"@stdlib/namespace/aliases" allocUnsafe,"@stdlib/buffer/alloc-unsafe" anova1,"@stdlib/stats/anova1" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index cbb9f4837863..6f5de2e299de 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ -{"AFINN_96":"@stdlib/datasets/afinn-96","AFINN_111":"@stdlib/datasets/afinn-111","aliases":"@stdlib/namespace/aliases","allocUnsafe":"@stdlib/buffer/alloc-unsafe","anova1":"@stdlib/stats/anova1","ANSCOMBES_QUARTET":"@stdlib/datasets/anscombes-quartet","any":"@stdlib/utils/any","anyBy":"@stdlib/utils/any-by","anyByAsync":"@stdlib/utils/async/any-by","anyByRight":"@stdlib/utils/any-by-right","anyByRightAsync":"@stdlib/utils/async/any-by-right","APERY":"@stdlib/constants/math/float64-apery","append":"@stdlib/utils/append","ARCH":"@stdlib/os/arch","argumentFunction":"@stdlib/utils/argument-function","ARGV":"@stdlib/process/argv","array":"@stdlib/ndarray/array","array2buffer":"@stdlib/buffer/from-array","array2iterator":"@stdlib/array/to-iterator","array2iteratorRight":"@stdlib/array/to-iterator-right","ArrayBuffer":"@stdlib/array/buffer","arraybuffer2buffer":"@stdlib/buffer/from-arraybuffer","arrayCtors":"@stdlib/array/ctors","arrayDataType":"@stdlib/array/dtype","arrayDataTypes":"@stdlib/array/dtypes","arrayMinDataType":"@stdlib/array/min-dtype","arrayNextDataType":"@stdlib/array/next-dtype","arrayPromotionRules":"@stdlib/array/promotion-rules","arraySafeCasts":"@stdlib/array/safe-casts","arraySameKindCasts":"@stdlib/array/same-kind-casts","arrayShape":"@stdlib/array/shape","arrayStream":"@stdlib/streams/node/from-array","arrayview2iterator":"@stdlib/array/to-view-iterator","arrayview2iteratorRight":"@stdlib/array/to-view-iterator-right","AsyncIteratorSymbol":"@stdlib/symbol/async-iterator","bartlettTest":"@stdlib/stats/bartlett-test","base.abs":"@stdlib/math/base/special/abs","base.abs2":"@stdlib/math/base/special/abs2","base.absdiff":"@stdlib/math/base/utils/absolute-difference","base.absInt32":"@stdlib/math/base/special/int32-abs","base.acos":"@stdlib/math/base/special/acos","base.acosh":"@stdlib/math/base/special/acosh","base.acoth":"@stdlib/math/base/special/acoth","base.acovercos":"@stdlib/math/base/special/acovercos","base.acoversin":"@stdlib/math/base/special/acoversin","base.ahavercos":"@stdlib/math/base/special/ahavercos","base.ahaversin":"@stdlib/math/base/special/ahaversin","base.asin":"@stdlib/math/base/special/asin","base.asinh":"@stdlib/math/base/special/asinh","base.atan":"@stdlib/math/base/special/atan","base.atan2":"@stdlib/math/base/special/atan2","base.atanh":"@stdlib/math/base/special/atanh","base.avercos":"@stdlib/math/base/special/avercos","base.aversin":"@stdlib/math/base/special/aversin","base.bernoulli":"@stdlib/math/base/special/bernoulli","base.besselj0":"@stdlib/math/base/special/besselj0","base.besselj1":"@stdlib/math/base/special/besselj1","base.bessely0":"@stdlib/math/base/special/bessely0","base.bessely1":"@stdlib/math/base/special/bessely1","base.beta":"@stdlib/math/base/special/beta","base.betainc":"@stdlib/math/base/special/betainc","base.betaincinv":"@stdlib/math/base/special/betaincinv","base.betaln":"@stdlib/math/base/special/betaln","base.binet":"@stdlib/math/base/special/binet","base.binomcoef":"@stdlib/math/base/special/binomcoef","base.binomcoefln":"@stdlib/math/base/special/binomcoefln","base.boxcox":"@stdlib/math/base/special/boxcox","base.boxcox1p":"@stdlib/math/base/special/boxcox1p","base.boxcox1pinv":"@stdlib/math/base/special/boxcox1pinv","base.boxcoxinv":"@stdlib/math/base/special/boxcoxinv","base.cabs":"@stdlib/math/base/complex/abs","base.cabs2":"@stdlib/math/base/complex/abs2","base.cadd":"@stdlib/math/base/complex/add","base.cbrt":"@stdlib/math/base/special/cbrt","base.cceil":"@stdlib/math/base/complex/ceil","base.cceiln":"@stdlib/math/base/complex/ceiln","base.ccis":"@stdlib/math/base/complex/cis","base.cdiv":"@stdlib/math/base/complex/divide","base.ceil":"@stdlib/math/base/special/ceil","base.ceil2":"@stdlib/math/base/special/ceil2","base.ceil10":"@stdlib/math/base/special/ceil10","base.ceilb":"@stdlib/math/base/special/ceilb","base.ceiln":"@stdlib/math/base/special/ceiln","base.ceilsd":"@stdlib/math/base/special/ceilsd","base.cexp":"@stdlib/math/base/complex/exp","base.cflipsign":"@stdlib/math/base/complex/flipsign","base.cfloor":"@stdlib/math/base/complex/floor","base.cfloorn":"@stdlib/math/base/complex/floorn","base.cinv":"@stdlib/math/base/complex/inv","base.clamp":"@stdlib/math/base/special/clamp","base.cmul":"@stdlib/math/base/complex/multiply","base.cneg":"@stdlib/math/base/complex/negate","base.continuedFraction":"@stdlib/math/base/tools/continued-fraction","base.copysign":"@stdlib/math/base/special/copysign","base.cos":"@stdlib/math/base/special/cos","base.cosh":"@stdlib/math/base/special/cosh","base.cosm1":"@stdlib/math/base/special/cosm1","base.cospi":"@stdlib/math/base/special/cospi","base.covercos":"@stdlib/math/base/special/covercos","base.coversin":"@stdlib/math/base/special/coversin","base.cphase":"@stdlib/math/base/complex/phase","base.cpolar":"@stdlib/math/base/complex/polar","base.cround":"@stdlib/math/base/complex/round","base.croundn":"@stdlib/math/base/complex/roundn","base.csignum":"@stdlib/math/base/complex/signum","base.csub":"@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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.json b/lib/node_modules/@stdlib/namespace/aliases/data/data.json index 9d4d76a01815..d3f48d1727cd 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.json +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index 17a744b54812..dc0facb43dfa 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1,5 +1,6 @@ AFINN_96 AFINN_111 +alias2pkg aliases allocUnsafe anova1 diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/a.js b/lib/node_modules/@stdlib/namespace/lib/namespace/a.js index 529a777dc4d3..514538af525e 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/a.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/a.js @@ -46,6 +46,18 @@ ns.push({ ] }); +ns.push({ + 'alias': 'alias2pkg', + 'path': '@stdlib/namespace/alias2pkg', + 'value': require( '@stdlib/namespace/alias2pkg' ), + 'type': 'Function', + 'related': [ + '@stdlib/namespace/alias2related', + '@stdlib/namespace/aliases', + '@stdlib/namespace/pkg2alias' + ] +}); + ns.push({ 'alias': 'aliases', 'path': '@stdlib/namespace/aliases', diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index 8b2f1d560e68..18460fb16ccd 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -26,6 +26,7 @@ var db = { "AFINN_96": "list = AFINN_96()\n", "AFINN_111": "list = AFINN_111()\n", + "alias2pkg": "v = alias2pkg( 'base.sin' )\n", "aliases": "o = aliases()\n", "allocUnsafe": "buf = allocUnsafe( 100 )\n", "anova1": "x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nf = [\n'control', 'treatA', 'treatB', 'treatC', 'control',\n'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n];\nout = anova1( x, f )\n", diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 9d7c5c451f54..a0be5a5db4ba 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -45,7 +45,7 @@ var GLOBALS = require( './globals.js' ); var debug = logger( 'repl:context' ); -// Cache references to module methods (WARNING: we use private methods exposed on the `Module` object; thus, breakage is possible!): +// Cache references to module methods (WARNING: use of *private* methods exposed on the `Module` object; thus, breakage is possible!): var resolveLookupPaths = Module._resolveLookupPaths; @@ -125,8 +125,6 @@ function createContext( repl ) { // TODO: add `example` command - // TODO: add `namespace` command - // TODO: add `isKeyword` command // TODO: add `save` command diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/drain.js b/lib/node_modules/@stdlib/repl/ctor/lib/drain.js index 1a579369c08d..768279c047df 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/drain.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/drain.js @@ -100,15 +100,15 @@ function drain( repl ) { code = repl._queue.pop(); debug( 'Command: %s', code.raw ); - // TODO: check whether command begins with `await` or `for await` (the latter would allow for updating the last line of output; e.g., an ASCII chart!); if so, then async processing and set `busy` to true; otherwise, assume sync processing - // Set the (non-standard) properties on the `RegExp` expression object to the cached matches: restoreRegExpMatches( repl._regexp ); + // TODO: handle async processing (if `code.async`, set `busy` to true; otherwise, assume sync processing) + // TODO: evaluate and determine whether to print result opts = { 'displayErrors': false, - 'breakOnSigint': true // Note: applies for only Node.js versions >=6.3.0 + 'breakOnSigint': true // Note: only applies for Node.js versions >=6.3.0 }; try { if ( repl._sandbox ) { diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js b/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js index c35fc0b25158..8d659bfd0dae 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js @@ -29,7 +29,7 @@ var MSG = [ ' example( alias ) Runs examples for a specified alias.', ' example( alias. ) Runs examples for a specified property.', '', - ' namespace() Lists namespace contents.', + ' aliases() Lists namespace contents.', ' alias2pkg( alias ) Converts an alias to a stdlib package name.', ' pkg2alias( pkg ) Converts a stdlib package name to an alias.', ' isKeyword( value ) Asserts whether a value is a reserved keyword/alias.', diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/process_line.js b/lib/node_modules/@stdlib/repl/ctor/lib/process_line.js index 176fdd63c5d9..1d3656059d0d 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/process_line.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/process_line.js @@ -77,6 +77,9 @@ function processLine( repl, line ) { line = '(' + line + ')\n'; isWrapped = true; } + // TODO: check whether line begins with (or includes?) `await` or `for await` (the latter would allow for updating the last line of output; e.g., an ASCII chart!); if async processing, then will need to transform the source code so that the returned promise is wrapped in order to invoke a callback/hook to indicate completion and a readiness to continue draining + code.async = false; + // Attempt to compile the command... while ( true ) { try { @@ -86,7 +89,7 @@ function processLine( repl, line ) { } else { // Note: `void 0` ensures that the compiled script does not return the string `'use strict'` when provided commands (statements/declarations) which do not return a value (e.g., `{}`): script = new vm.Script( '\'use strict\'; void 0;\n'+line, opts ); - code.silent = line.charCodeAt( line.length-1 ) === SEMICOLON; // eslint-disable-line max-len + code.silent = line.charCodeAt( line.length-1 ) === SEMICOLON; } code.compiled = script; } catch ( error ) { diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index cf6f268a64bb..d4de6649e415 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -26,7 +26,8 @@ var db = { "AFINN_96": "\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n", "AFINN_111": "\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n", - "aliases": "\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n", + "alias2pkg": "\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n aliases\n", + "aliases": "\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n See Also\n --------\n alias2pkg\n", "allocUnsafe": "\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n", "anova1": "\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n", "ANSCOMBES_QUARTET": "\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n", From b5b9382225564a5b2188fc3045e88447d2bb90f0 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 19:30:44 -0700 Subject: [PATCH 046/142] Fix example --- lib/node_modules/@stdlib/namespace/alias2pkg/lib/main.js | 2 -- 1 file changed, 2 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/lib/main.js b/lib/node_modules/@stdlib/namespace/alias2pkg/lib/main.js index 32774f28106b..911b0b8c4b3a 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/lib/main.js +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/lib/main.js @@ -35,8 +35,6 @@ var ALIAS_TO_PKG = require( './../data/data.json' ); * @returns {(string|null)} package name * * @example -* var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); -* * var v = alias2pkg( 'base.sin' ); * // returns '@stdlib/math/base/special/sin' */ From d531f0c1202da489c3f4f3391c0f2b8aa08048d7 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 19:38:20 -0700 Subject: [PATCH 047/142] Add utility to map a package name to an alias --- .../@stdlib/namespace/pkg2alias/README.md | 179 ++ .../pkg2alias/benchmark/benchmark.js | 55 + .../@stdlib/namespace/pkg2alias/bin/cli | 64 + .../@stdlib/namespace/pkg2alias/data/data.csv | 1885 +++++++++++++++++ .../namespace/pkg2alias/data/data.json | 1 + .../@stdlib/namespace/pkg2alias/docs/repl.txt | 21 + .../namespace/pkg2alias/docs/types/index.d.ts | 36 + .../namespace/pkg2alias/docs/types/test.ts | 44 + .../namespace/pkg2alias/docs/usage.txt | 8 + .../namespace/pkg2alias/etc/cli_opts.json | 15 + .../namespace/pkg2alias/examples/index.js | 43 + .../@stdlib/namespace/pkg2alias/lib/index.js | 40 + .../@stdlib/namespace/pkg2alias/lib/main.js | 54 + .../@stdlib/namespace/pkg2alias/package.json | 67 + .../namespace/pkg2alias/scripts/build.js | 82 + .../namespace/pkg2alias/test/test.cli.js | 181 ++ .../@stdlib/namespace/pkg2alias/test/test.js | 96 + 17 files changed, 2871 insertions(+) create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/README.md create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/benchmark/benchmark.js create mode 100755 lib/node_modules/@stdlib/namespace/pkg2alias/bin/cli create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/docs/usage.txt create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/etc/cli_opts.json create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/examples/index.js create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/lib/index.js create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/lib/main.js create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/package.json create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/scripts/build.js create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/test/test.cli.js create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/test/test.js diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/README.md b/lib/node_modules/@stdlib/namespace/pkg2alias/README.md new file mode 100644 index 000000000000..e9fb9be33663 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/README.md @@ -0,0 +1,179 @@ + + +# pkg2alias + +> Return the alias associated with a specified package name. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var pkg2alias = require( '@stdlib/namespace/pkg2alias' ); +``` + +#### pkg2alias( pkg ) + +Returns the alias associated with a specified package name. + +```javascript +var v = pkg2alias( '@stdlib/math/base/special/sin' ); +// returns 'base.sin' +``` + +If provided an unrecognized `pkg`, the function returns `null`. + +```javascript +var v = pkg2alias( 'unrecognized_pkg_beep_boop_bop_bip' ); +// returns null +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var pkg2alias = require( '@stdlib/namespace/pkg2alias' ); + +var list; +var len; +var idx; +var v1; +var v2; +var i; + +list = aliases(); +len = list.length; + +// Round-trip from alias-to-pkg-to-alias... +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len ); + v1 = alias2pkg( list[ idx ] ); + v2 = pkg2alias( v1 ); + console.log( 'alias: %s. pkg: %s.', list[ idx ], v1 ); + console.log( 'pkg: %s. alias: %s.', v1, v2 ); +} +``` + +
+ + + + + +* * * + +
+ +## CLI + + + +
+ +### Usage + +```text +Usage: stdlib-pkg2alias [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```bash +$ stdlib-pkg2alias '@stdlib/math/base/special/sin' +base.sin +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/benchmark/benchmark.js b/lib/node_modules/@stdlib/namespace/pkg2alias/benchmark/benchmark.js new file mode 100644 index 000000000000..f22004454776 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/benchmark/benchmark.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var pkg = require( './../package.json' ).name; +var pkg2alias = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var v; + var i; + + values = [ + '@stdlib/math/base/special/sin', + '@stdlib/math/base/special/abs', + '@stdlib/math/base/special/cos' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = pkg2alias( values[ i%values.length ] ); + if ( typeof v !== 'string' ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( v ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/bin/cli b/lib/node_modules/@stdlib/namespace/pkg2alias/bin/cli new file mode 100755 index 000000000000..568fbb91b442 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/bin/cli @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var readFileSync = require( '@stdlib/fs/read-file' ).sync; +var CLI = require( '@stdlib/tools/cli' ); +var pkg2alias = require( './../lib' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var args; + var cli; + var out; + + // Create a command-line interface: + cli = new CLI({ + 'pkg': require( './../package.json' ), + 'options': require( './../etc/cli_opts.json' ), + 'help': readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }) + }); + + // Get any provided command-line arguments: + args = cli.args(); + + // Resolve a provided package name to an alias... + out = pkg2alias( args[ 0 ] ); + if ( out ) { + console.log( out ); // eslint-disable-line no-console + } else { + cli.exit( 1 ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv new file mode 100644 index 000000000000..6707bae3e48e --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -0,0 +1,1885 @@ +"@stdlib/datasets/afinn-96",AFINN_96 +"@stdlib/datasets/afinn-111",AFINN_111 +"@stdlib/namespace/alias2pkg",alias2pkg +"@stdlib/namespace/aliases",aliases +"@stdlib/buffer/alloc-unsafe",allocUnsafe +"@stdlib/stats/anova1",anova1 +"@stdlib/datasets/anscombes-quartet",ANSCOMBES_QUARTET +"@stdlib/utils/any",any +"@stdlib/utils/any-by",anyBy +"@stdlib/utils/async/any-by",anyByAsync +"@stdlib/utils/any-by-right",anyByRight +"@stdlib/utils/async/any-by-right",anyByRightAsync +"@stdlib/constants/math/float64-apery",APERY +"@stdlib/utils/append",append +"@stdlib/os/arch",ARCH +"@stdlib/utils/argument-function",argumentFunction +"@stdlib/process/argv",ARGV +"@stdlib/ndarray/array",array +"@stdlib/buffer/from-array",array2buffer +"@stdlib/array/to-iterator",array2iterator +"@stdlib/array/to-iterator-right",array2iteratorRight +"@stdlib/array/buffer",ArrayBuffer +"@stdlib/buffer/from-arraybuffer",arraybuffer2buffer +"@stdlib/array/ctors",arrayCtors +"@stdlib/array/dtype",arrayDataType +"@stdlib/array/dtypes",arrayDataTypes +"@stdlib/array/min-dtype",arrayMinDataType +"@stdlib/array/next-dtype",arrayNextDataType +"@stdlib/array/promotion-rules",arrayPromotionRules +"@stdlib/array/safe-casts",arraySafeCasts +"@stdlib/array/same-kind-casts",arraySameKindCasts +"@stdlib/array/shape",arrayShape +"@stdlib/streams/node/from-array",arrayStream +"@stdlib/array/to-view-iterator",arrayview2iterator +"@stdlib/array/to-view-iterator-right",arrayview2iteratorRight +"@stdlib/symbol/async-iterator",AsyncIteratorSymbol +"@stdlib/stats/bartlett-test",bartlettTest +"@stdlib/math/base/special/abs",base.abs +"@stdlib/math/base/special/abs2",base.abs2 +"@stdlib/math/base/utils/absolute-difference",base.absdiff +"@stdlib/math/base/special/int32-abs",base.absInt32 +"@stdlib/math/base/special/acos",base.acos +"@stdlib/math/base/special/acosh",base.acosh +"@stdlib/math/base/special/acoth",base.acoth +"@stdlib/math/base/special/acovercos",base.acovercos +"@stdlib/math/base/special/acoversin",base.acoversin +"@stdlib/math/base/special/ahavercos",base.ahavercos +"@stdlib/math/base/special/ahaversin",base.ahaversin +"@stdlib/math/base/special/asin",base.asin 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/docs/repl.txt b/lib/node_modules/@stdlib/namespace/pkg2alias/docs/repl.txt new file mode 100644 index 000000000000..9cebfa491a1b --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/docs/repl.txt @@ -0,0 +1,21 @@ + +{{alias}}( pkg ) + Returns the alias associated with a specified package name. + + Parameters + ---------- + pkg: string + Package name. + + Returns + ------- + out: string|null + Alias. + + Examples + -------- + > var v = {{alias}}( '@stdlib/math/base/special/sin' ) + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/docs/types/index.d.ts b/lib/node_modules/@stdlib/namespace/pkg2alias/docs/types/index.d.ts new file mode 100644 index 000000000000..0a93f2924f3d --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/docs/types/index.d.ts @@ -0,0 +1,36 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Returns an alias associated with a specified package name. +* +* @param pkg - package name +* @returns alias +* +* @example +* var v = pkg2alias( '@stdlib/math/base/special/sin' ); +* // returns 'base.sin' +*/ +declare function pkg2alias( pkg: string ): string | null; + + +// EXPORTS // + +export = pkg2alias; diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/docs/types/test.ts b/lib/node_modules/@stdlib/namespace/pkg2alias/docs/types/test.ts new file mode 100644 index 000000000000..6f1c4c053049 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import pkg2alias = require( './index' ); + + +// TESTS // + +// The function returns a string or null... +{ + pkg2alias( '@stdlib/math/base/special/sin' ); // $ExpectType string | null +} + +// The compiler throws an error if the function is not provided a string... +{ + pkg2alias( 5 ); // $ExpectError + pkg2alias( true ); // $ExpectError + pkg2alias( false ); // $ExpectError + pkg2alias( null ); // $ExpectError + pkg2alias( undefined ); // $ExpectError + pkg2alias( [] ); // $ExpectError + pkg2alias( {} ); // $ExpectError + pkg2alias( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + pkg2alias( '@stdlib/math/base/special/sin', 'beep' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/docs/usage.txt b/lib/node_modules/@stdlib/namespace/pkg2alias/docs/usage.txt new file mode 100644 index 000000000000..d3a79ecac163 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/docs/usage.txt @@ -0,0 +1,8 @@ + +Usage: stdlib-pkg2alias [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. + diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/etc/cli_opts.json b/lib/node_modules/@stdlib/namespace/pkg2alias/etc/cli_opts.json new file mode 100644 index 000000000000..92119c456962 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/etc/cli_opts.json @@ -0,0 +1,15 @@ +{ + "string": [], + "boolean": [ + "help", + "version" + ], + "alias": { + "help": [ + "h" + ], + "version": [ + "V" + ] + } +} diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/examples/index.js b/lib/node_modules/@stdlib/namespace/pkg2alias/examples/index.js new file mode 100644 index 000000000000..f95ff36c579e --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/examples/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var pkg2alias = require( './../lib' ); + +var list; +var len; +var idx; +var v1; +var v2; +var i; + +list = aliases(); +len = list.length; + +// Round-trip from alias-to-pkg-to-alias... +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len ); + v1 = alias2pkg( list[ idx ] ); + v2 = pkg2alias( v1 ); + console.log( 'alias: %s. pkg: %s.', list[ idx ], v1 ); + console.log( 'pkg: %s. alias: %s.', v1, v2 ); +} diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/lib/index.js b/lib/node_modules/@stdlib/namespace/pkg2alias/lib/index.js new file mode 100644 index 000000000000..71ddd24f2427 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the alias associated with a specified package name. +* +* @module @stdlib/namespace/pkg2alias +* +* @example +* var pkg2alias = require( '@stdlib/namespace/pkg2alias' ); +* +* var v = pkg2alias( '@stdlib/math/base/special/sin' ); +* // returns 'base.sin' +*/ + +// MODULES // + +var pkg2alias = require( './main.js' ); + + +// EXPORTS // + +module.exports = pkg2alias; diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/lib/main.js b/lib/node_modules/@stdlib/namespace/pkg2alias/lib/main.js new file mode 100644 index 000000000000..fd8ea0b9cb09 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/lib/main.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var PKG_TO_ALIAS = require( './../data/data.json' ); + + +// MAIN // + +/** +* Returns the alias associated with a specified package name. +* +* @param {string} pkg - package name +* @throws {TypeError} must provide a string +* @returns {(string|null)} alias +* +* @example +* var v = pkg2alias( '@stdlib/math/base/special/sin' ); +* // returns 'base.sin' +*/ +function pkg2alias( pkg ) { + if ( !isString( pkg ) ) { + throw new TypeError( 'invalid argument. Must provide a string. Value: `' + pkg + '`.' ); + } + if ( hasOwnProp( PKG_TO_ALIAS, pkg ) ) { + return PKG_TO_ALIAS[ pkg ]; + } + return null; +} + + +// EXPORTS // + +module.exports = pkg2alias; diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/package.json b/lib/node_modules/@stdlib/namespace/pkg2alias/package.json new file mode 100644 index 000000000000..365f6a9438e3 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/namespace/pkg2alias", + "version": "0.0.0", + "description": "Return the alias associated with a specified package name.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "bin": { + "stdlib-pkg2alias": "./bin/cli" + }, + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "bin": "./bin", + "data": "./data", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "standard", + "library", + "lib", + "aliases", + "alias", + "namespace", + "package", + "name", + "pkg" + ] +} diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/scripts/build.js b/lib/node_modules/@stdlib/namespace/pkg2alias/scripts/build.js new file mode 100644 index 000000000000..085da28c8de8 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/scripts/build.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var logger = require( 'debug' ); +var writeFile = require( '@stdlib/fs/write-file' ).sync; +var namespace = require( '@stdlib/namespace' ); +var objectKeys = require( '@stdlib/utils/keys' ); + + +// VARIABLES // + +var debug = logger( 'namespace:pkg2alias:build' ); + +// Output file paths: +var OUTPUT_JSON = resolve( __dirname, '..', 'data', 'data.json' ); +var OUTPUT_CSV = resolve( __dirname, '..', 'data', 'data.csv' ); + + +// FUNCTIONS // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var fopts; + var keys; + var json; + var csv; + var ns; + var i; + + debug( 'Extracting namespace package names and aliases...' ); + ns = namespace(); + json = {}; + for ( i = 0; i < ns.length; i++ ) { + json[ ns[i].path ] = ns[ i ].alias; + } + + debug( 'Writing to JSON file...' ); + fopts = { + 'encoding': 'utf8' + }; + writeFile( OUTPUT_JSON, JSON.stringify( json ), fopts ); + + debug( 'Writing to CSV file...' ); + fopts = { + 'encoding': 'utf8' + }; + keys = objectKeys( json ); + csv = ''; + for ( i = 0; i < keys.length; i++ ) { + csv += '"' + keys[ i ] + '",' + json[ keys[i] ] + '\n'; // Note: ensures trailing newline + } + writeFile( OUTPUT_CSV, csv, fopts ); +} + + +// MAIN // + +main(); diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/test/test.cli.js b/lib/node_modules/@stdlib/namespace/pkg2alias/test/test.cli.js new file mode 100644 index 000000000000..8a62431e4ff4 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/test/test.cli.js @@ -0,0 +1,181 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var exec = require( 'child_process' ).exec; +var tape = require( 'tape' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); +var readFileSync = require( '@stdlib/fs/read-file' ).sync; + + +// VARIABLES // + +var fpath = resolve( __dirname, '..', 'bin', 'cli' ); +var opts = { + 'skip': IS_BROWSER || IS_WINDOWS +}; + + +// FIXTURES // + +var PKG_VERSION = require( './../package.json' ).version; + + +// TESTS // + +tape( 'command-line interface', function test( t ) { + t.ok( true, __filename ); + t.end(); +}); + +tape( 'when invoked with a `--help` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '--help' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-h` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '-h' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `--version` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '--version' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-V` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '-V' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'the command-line interface prints an alias', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '@stdlib/math/base/special/sin' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), 'base.sin\n', 'prints expected value' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + } + t.end(); + } +}); + +tape( 'if unable to resolve an alias, the command-line interface sets a non-zero exit code', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + 'fjaldfjadljfeoejreandfljasdfjadsfjs' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.pass( error.message ); + t.strictEqual( error.code, 1, 'expected exit code' ); + } + t.strictEqual( stdout.toString(), '', 'does not print to` stdout`' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + t.end(); + } +}); diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/test/test.js b/lib/node_modules/@stdlib/namespace/pkg2alias/test/test.js new file mode 100644 index 000000000000..8ff0585efe33 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/test/test.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var DATA = require( './../data/data.json' ); +var pkg2alias = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof pkg2alias, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a string', function test( t ) { + var values; + var i; + + values = [ + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + pkg2alias( value ); + }; + } +}); + +tape( 'the function returns an alias', function test( t ) { + var expected; + var actual; + var list; + var pkg; + var i; + + list = aliases(); + for ( i = 0; i < list.length; i++ ) { + pkg = alias2pkg( list[i] ); + expected = DATA[ pkg ]; + actual = pkg2alias( pkg ); + t.strictEqual( typeof actual, 'string', 'returns a string' ); + t.strictEqual( actual, expected, 'returns expected value for '+pkg ); + } + t.end(); +}); + +tape( 'the function returns `null` if provided an unrecognized package name', function test( t ) { + var values; + var i; + + values = [ + 'adfkaljdfdsafs', + 'adklfadjflajdslfjalsdf', + 'adflkajdlkfjasdlkfjsadlkfjlasdjflsdjfla' + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( pkg2alias( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); From b936ee5875aff4e77e6d3b75a7a9c8f3d4a0dce8 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 19:41:59 -0700 Subject: [PATCH 048/142] Add task for building a mapping between package names and aliases --- tools/make/lib/docs/repl.mk | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/tools/make/lib/docs/repl.mk b/tools/make/lib/docs/repl.mk index ef608dba9734..3b0c2bb6b802 100644 --- a/tools/make/lib/docs/repl.mk +++ b/tools/make/lib/docs/repl.mk @@ -30,6 +30,9 @@ REPL_BUILD_ALIASES ?= $(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js # Define the path to the executable for mapping REPL aliases to package names: REPL_BUILD_ALIAS2PKG ?= $(SRC_DIR)/@stdlib/namespace/alias2pkg/scripts/build.js +# Define the path to the executable for mapping REPL package names to aliases: +REPL_BUILD_PKG2ALIAS ?= $(SRC_DIR)/@stdlib/namespace/pkg2alias/scripts/build.js + # TARGETS # @@ -37,7 +40,7 @@ REPL_BUILD_ALIAS2PKG ?= $(SRC_DIR)/@stdlib/namespace/alias2pkg/scripts/build.js # # This target generates REPL documentation. -repl-docs: repl-help repl-examples repl-aliases repl-alias2pkg +repl-docs: repl-help repl-examples repl-aliases repl-alias2pkg repl-pkg2alias .PHONY: repl-docs @@ -80,3 +83,13 @@ repl-alias2pkg: $(NODE_MODULES) $(REPL_BUILD_ALIAS2PKG) $(QUIET) $(NODE) $(REPL_BUILD_ALIAS2PKG) .PHONY: repl-alias2pkg + + +# Build the mapping between REPL package names and aliases. +# +# This target rebuilds the REPL database. + +repl-pkg2alias: $(NODE_MODULES) $(REPL_BUILD_PKG2ALIAS) + $(QUIET) $(NODE) $(REPL_BUILD_PKG2ALIAS) + +.PHONY: repl-pkg2alias From c4ca79ecbcf04df6ac4b8eb8b912cbb0b675f0df Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 19:42:53 -0700 Subject: [PATCH 049/142] Update namespace --- .../@stdlib/namespace/alias2pkg/data/data.csv | 1 + .../@stdlib/namespace/alias2pkg/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.txt | 1 + .../@stdlib/namespace/lib/namespace/p.js | 12 ++++++++++++ .../@stdlib/namespace/pkg2alias/data/data.csv | 1 + .../@stdlib/namespace/pkg2alias/data/data.json | 2 +- lib/node_modules/@stdlib/repl/code-blocks/lib/db.js | 1 + lib/node_modules/@stdlib/repl/help/lib/db.js | 5 +++-- 9 files changed, 22 insertions(+), 5 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index fcbec6faa200..8e5fbb33c991 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1582,6 +1582,7 @@ PI_SQUARED,"@stdlib/constants/math/float64-pi-squared" pick,"@stdlib/utils/pick" pickBy,"@stdlib/utils/pick-by" PINF,"@stdlib/constants/math/float64-pinf" +pkg2alias,"@stdlib/namespace/pkg2alias" PLATFORM,"@stdlib/os/platform" plot,"@stdlib/plot" Plot,"@stdlib/plot/ctor" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index 6f5de2e299de..4771e8ebea87 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ -{"AFINN_96":"@stdlib/datasets/afinn-96","AFINN_111":"@stdlib/datasets/afinn-111","alias2pkg":"@stdlib/namespace/alias2pkg","aliases":"@stdlib/namespace/aliases","allocUnsafe":"@stdlib/buffer/alloc-unsafe","anova1":"@stdlib/stats/anova1","ANSCOMBES_QUARTET":"@stdlib/datasets/anscombes-quartet","any":"@stdlib/utils/any","anyBy":"@stdlib/utils/any-by","anyByAsync":"@stdlib/utils/async/any-by","anyByRight":"@stdlib/utils/any-by-right","anyByRightAsync":"@stdlib/utils/async/any-by-right","APERY":"@stdlib/constants/math/float64-apery","append":"@stdlib/utils/append","ARCH":"@stdlib/os/arch","argumentFunction":"@stdlib/utils/argument-function","ARGV":"@stdlib/process/argv","array":"@stdlib/ndarray/array","array2buffer":"@stdlib/buffer/from-array","array2iterator":"@stdlib/array/to-iterator","array2iteratorRight":"@stdlib/array/to-iterator-right","ArrayBuffer":"@stdlib/array/buffer","arraybuffer2buffer":"@stdlib/buffer/from-arraybuffer","arrayCtors":"@stdlib/array/ctors","arrayDataType":"@stdlib/array/dtype","arrayDataTypes":"@stdlib/array/dtypes","arrayMinDataType":"@stdlib/array/min-dtype","arrayNextDataType":"@stdlib/array/next-dtype","arrayPromotionRules":"@stdlib/array/promotion-rules","arraySafeCasts":"@stdlib/array/safe-casts","arraySameKindCasts":"@stdlib/array/same-kind-casts","arrayShape":"@stdlib/array/shape","arrayStream":"@stdlib/streams/node/from-array","arrayview2iterator":"@stdlib/array/to-view-iterator","arrayview2iteratorRight":"@stdlib/array/to-view-iterator-right","AsyncIteratorSymbol":"@stdlib/symbol/async-iterator","bartlettTest":"@stdlib/stats/bartlett-test","base.abs":"@stdlib/math/base/special/abs","base.abs2":"@stdlib/math/base/special/abs2","base.absdiff":"@stdlib/math/base/utils/absolute-difference","base.absInt32":"@stdlib/math/base/special/int32-abs","base.acos":"@stdlib/math/base/special/acos","base.acosh":"@stdlib/math/base/special/acosh","base.acoth":"@stdlib/math/base/special/acoth","base.acovercos":"@stdlib/math/base/special/acovercos","base.acoversin":"@stdlib/math/base/special/acoversin","base.ahavercos":"@stdlib/math/base/special/ahavercos","base.ahaversin":"@stdlib/math/base/special/ahaversin","base.asin":"@stdlib/math/base/special/asin","base.asinh":"@stdlib/math/base/special/asinh","base.atan":"@stdlib/math/base/special/atan","base.atan2":"@stdlib/math/base/special/atan2","base.atanh":"@stdlib/math/base/special/atanh","base.avercos":"@stdlib/math/base/special/avercos","base.aversin":"@stdlib/math/base/special/aversin","base.bernoulli":"@stdlib/math/base/special/bernoulli","base.besselj0":"@stdlib/math/base/special/besselj0","base.besselj1":"@stdlib/math/base/special/besselj1","base.bessely0":"@stdlib/math/base/special/bessely0","base.bessely1":"@stdlib/math/base/special/bessely1","base.beta":"@stdlib/math/base/special/beta","base.betainc":"@stdlib/math/base/special/betainc","base.betaincinv":"@stdlib/math/base/special/betaincinv","base.betaln":"@stdlib/math/base/special/betaln","base.binet":"@stdlib/math/base/special/binet","base.binomcoef":"@stdlib/math/base/special/binomcoef","base.binomcoefln":"@stdlib/math/base/special/binomcoefln","base.boxcox":"@stdlib/math/base/special/boxcox","base.boxcox1p":"@stdlib/math/base/special/boxcox1p","base.boxcox1pinv":"@stdlib/math/base/special/boxcox1pinv","base.boxcoxinv":"@stdlib/math/base/special/boxcoxinv","base.cabs":"@stdlib/math/base/complex/abs","base.cabs2":"@stdlib/math/base/complex/abs2","base.cadd":"@stdlib/math/base/complex/add","base.cbrt":"@stdlib/math/base/special/cbrt","base.cceil":"@stdlib/math/base/complex/ceil","base.cceiln":"@stdlib/math/base/complex/ceiln","base.ccis":"@stdlib/math/base/complex/cis","base.cdiv":"@stdlib/math/base/complex/divide","base.ceil":"@stdlib/math/base/special/ceil","base.ceil2":"@stdlib/math/base/special/ceil2","base.ceil10":"@stdlib/math/base/special/ceil10","base.ceilb":"@stdlib/math/base/special/ceilb","base.ceiln":"@stdlib/math/base/special/ceiln","base.ceilsd":"@stdlib/math/base/special/ceilsd","base.cexp":"@stdlib/math/base/complex/exp","base.cflipsign":"@stdlib/math/base/complex/flipsign","base.cfloor":"@stdlib/math/base/complex/floor","base.cfloorn":"@stdlib/math/base/complex/floorn","base.cinv":"@stdlib/math/base/complex/inv","base.clamp":"@stdlib/math/base/special/clamp","base.cmul":"@stdlib/math/base/complex/multiply","base.cneg":"@stdlib/math/base/complex/negate","base.continuedFraction":"@stdlib/math/base/tools/continued-fraction","base.copysign":"@stdlib/math/base/special/copysign","base.cos":"@stdlib/math/base/special/cos","base.cosh":"@stdlib/math/base/special/cosh","base.cosm1":"@stdlib/math/base/special/cosm1","base.cospi":"@stdlib/math/base/special/cospi","base.covercos":"@stdlib/math/base/special/covercos","base.coversin":"@stdlib/math/base/special/coversin","base.cphase":"@stdlib/math/base/complex/phase","base.cpolar":"@stdlib/math/base/complex/polar","base.cround":"@stdlib/math/base/complex/round","base.croundn":"@stdlib/math/base/complex/roundn","base.csignum":"@stdli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andom.boxMuller":"@stdlib/random/base/box-muller","base.random.cauchy":"@stdlib/random/base/cauchy","base.random.chi":"@stdlib/random/base/chi","base.random.chisquare":"@stdlib/random/base/chisquare","base.random.cosine":"@stdlib/random/base/cosine","base.random.discreteUniform":"@stdlib/random/base/discrete-uniform","base.random.erlang":"@stdlib/random/base/erlang","base.random.exponential":"@stdlib/random/base/exponential","base.random.f":"@stdlib/random/base/f","base.random.frechet":"@stdlib/random/base/frechet","base.random.gamma":"@stdlib/random/base/gamma","base.random.geometric":"@stdlib/random/base/geometric","base.random.gumbel":"@stdlib/random/base/gumbel","base.random.hypergeometric":"@stdlib/random/base/hypergeometric","base.random.improvedZiggurat":"@stdlib/random/base/improved-ziggurat","base.random.invgamma":"@stdlib/random/base/invgamma","base.random.kumaraswamy":"@stdlib/random/base/kumaraswamy","base.random.laplace":"@stdlib/random/base/laplace","base.random.levy":"@stdlib/random/base/levy","base.random.logistic":"@stdlib/random/base/logistic","base.random.lognormal":"@stdlib/random/base/lognormal","base.random.minstd":"@stdlib/random/base/minstd","base.random.minstdShuffle":"@stdlib/random/base/minstd-shuffle","base.random.mt19937":"@stdlib/random/base/mt19937","base.random.negativeBinomial":"@stdlib/random/base/negative-binomial","base.random.normal":"@stdlib/random/base/normal","base.random.pareto1":"@stdlib/random/base/pareto-type1","base.random.poisson":"@stdlib/random/base/poisson","base.random.randi":"@stdlib/random/base/randi","base.random.randn":"@stdlib/random/base/randn","base.random.randu":"@stdlib/random/base/randu","base.random.rayleigh":"@stdlib/random/base/rayleigh","base.random.t":"@stdlib/random/base/t","base.random.triangular":"@stdlib/random/base/triangular","base.random.uniform":"@stdlib/random/base/uniform","base.random.weibull":"@stdlib/random/base/weibull","base.reldiff":"@stdlib/math/base/utils/relative-difference","base.rempio2":"@stdlib/math/base/special/rempio2","base.risingFactorial":"@stdlib/math/base/special/rising-factorial","base.rotl32":"@stdlib/number/uint32/base/rotl","base.rotr32":"@stdlib/number/uint32/base/rotr","base.round":"@stdlib/math/base/special/round","base.round2":"@stdlib/math/base/special/round2","base.round10":"@stdlib/math/base/special/round10","base.roundb":"@stdlib/math/base/special/roundb","base.roundn":"@stdlib/math/base/special/roundn","base.roundsd":"@stdlib/math/base/special/roundsd","base.rsqrt":"@stdlib/math/base/special/rsqrt","base.sasum":"@stdlib/blas/base/sasum","base.saxpy":"@stdlib/blas/base/saxpy","base.scopy":"@stdlib/blas/base/scopy","base.setHighWord":"@stdlib/number/float64/base/set-high-word","base.setLowWord":"@stdlib/number/float64/base/set-low-word","base.sici":"@stdlib/math/base/special/sici","base.signbit":"@stdlib/number/float64/base/signbit","base.signbitf":"@stdlib/number/float32/base/signbit","base.significandf":"@stdlib/number/float32/base/significand","base.signum":"@stdlib/math/base/special/signum","base.sin":"@stdlib/math/base/special/sin","base.sinc":"@stdlib/math/base/special/sinc","base.sincos":"@stdlib/math/base/special/sincos","base.sincospi":"@stdlib/math/base/special/sincospi","base.sinh":"@stdlib/math/base/special/sinh","base.sinpi":"@stdlib/math/base/special/sinpi","base.spence":"@stdlib/math/base/special/spence","base.sqrt":"@stdlib/math/base/special/sqrt","base.sqrt1pm1":"@stdlib/math/base/special/sqrt1pm1","base.sumSeries":"@stdlib/math/base/tools/sum-series","base.tan":"@stdlib/math/base/special/tan","base.tanh":"@stdlib/math/base/special/tanh","base.toBinaryString":"@stdlib/number/float64/base/to-binary-string","base.toBinaryStringf":"@stdlib/number/float32/base/to-binary-string","base.toBinaryStringUint8":"@stdlib/number/uint8/base/to-binary-string","base.toBinaryStringUint16":"@stdlib/number/uint16/base/to-binary-string","base.toBinaryStringUint32":"@stdlib/number/uint32/base/to-binary-string","base.toWordf":"@stdlib/number/float32/base/to-word","base.toWords":"@stdlib/number/float64/base/to-words","base.trigamma":"@stdlib/math/base/special/trigamma","base.trunc":"@stdlib/math/base/special/trunc","base.trunc2":"@stdlib/math/base/special/trunc2","base.trunc10":"@stdlib/math/base/special/trunc10","base.truncb":"@stdlib/math/base/special/truncb","base.truncn":"@stdlib/math/base/special/truncn","base.truncsd":"@stdlib/math/base/special/truncsd","base.uimul":"@stdlib/math/base/special/uimul","base.uimuldw":"@stdlib/math/base/special/uimuldw","base.uint32ToInt32":"@stdlib/number/uint32/base/to-int32","base.vercos":"@stdlib/math/base/special/vercos","base.versin":"@stdlib/math/base/special/versin","base.wrap":"@stdlib/math/base/special/wrap","base.xlog1py":"@stdlib/math/base/special/xlog1py","base.xlogy":"@stdlib/math/base/special/xlogy","base.zeta":"@stdlib/math/base/special/riemann-zeta","BERNDT_CPS_WAGES_1985":"@stdlib/datasets/berndt-cps-wages-1985","bifurcate":"@stdlib/utils/bifurcate","bifur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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index dc0facb43dfa..cf12cef10de2 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1582,6 +1582,7 @@ PI_SQUARED pick pickBy PINF +pkg2alias PLATFORM plot Plot diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/p.js b/lib/node_modules/@stdlib/namespace/lib/namespace/p.js index e740126fd5a0..90ad728c6832 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/p.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/p.js @@ -224,6 +224,18 @@ ns.push({ ] }); +ns.push({ + 'alias': 'pkg2alias', + 'path': '@stdlib/namespace/pkg2alias', + 'value': require( '@stdlib/namespace/pkg2alias' ), + 'type': 'Function', + 'related': [ + '@stdlib/namespace/alias2pkg', + '@stdlib/namespace/aliases', + '@stdlib/namespace/pkg2related' + ] +}); + ns.push({ 'alias': 'PLATFORM', 'path': '@stdlib/os/platform', diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index 6707bae3e48e..ce94add28746 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -1582,6 +1582,7 @@ "@stdlib/utils/pick",pick "@stdlib/utils/pick-by",pickBy "@stdlib/constants/math/float64-pinf",PINF +"@stdlib/namespace/pkg2alias",pkg2alias "@stdlib/os/platform",PLATFORM "@stdlib/plot",plot "@stdlib/plot/ctor",Plot diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index af718fb729b8..0856d50f91c2 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ 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regexp/extended-length-path":"RE_EXTENDED_LENGTH_PATH","@stdlib/regexp/extname":"RE_EXTNAME","@stdlib/regexp/extname-posix":"RE_EXTNAME_POSIX","@stdlib/regexp/extname-windows":"RE_EXTNAME_WINDOWS","@stdlib/regexp/filename":"RE_FILENAME","@stdlib/regexp/filename-posix":"RE_FILENAME_POSIX","@stdlib/regexp/filename-windows":"RE_FILENAME_WINDOWS","@stdlib/regexp/function-name":"RE_FUNCTION_NAME","@stdlib/regexp/native-function":"RE_NATIVE_FUNCTION","@stdlib/regexp/regexp":"RE_REGEXP","@stdlib/regexp/unc-path":"RE_UNC_PATH","@stdlib/regexp/utf16-surrogate-pair":"RE_UTF16_SURROGATE_PAIR","@stdlib/regexp/utf16-unpaired-surrogate":"RE_UTF16_UNPAIRED_SURROGATE","@stdlib/regexp/whitespace":"RE_WHITESPACE","@stdlib/fs/read-dir":"readDir","@stdlib/fs/read-file":"readFile","@stdlib/fs/read-file-list":"readFileList","@stdlib/fs/read-json":"readJSON","@stdlib/fs/read-wasm":"readWASM","@stdlib/complex/real":"real","@stdlib/utils/real-max":"realmax","@stdlib/utils/real-min":"realmin","@stdlib/utils/reduce":"reduce","@stdlib/utils/async/reduce":"reduceAsync","@stdlib/utils/reduce-right":"reduceRight","@stdlib/utils/async/reduce-right":"reduceRightAsync","@stdlib/utils/regexp-from-string":"reFromString","@stdlib/complex/reim":"reim","@stdlib/string/remove-first":"removeFirst","@stdlib/string/remove-last":"removeLast","@stdlib/string/remove-punctuation":"removePunctuation","@stdlib/string/remove-utf8-bom":"removeUTF8BOM","@stdlib/string/remove-words":"removeWords","@stdlib/fs/rename":"rename","@stdlib/utils/reorder-arguments":"reorderArguments","@stdlib/string/repeat":"repeat","@stdlib/string/replace":"replace","@stdlib/utils/escape-regexp-string":"rescape","@stdlib/fs/resolve-parent-path":"resolveParentPath","@stdlib/utils/reverse-arguments":"reverseArguments","@stdlib/string/reverse":"reverseString","@stdlib/random/base/reviver":"reviveBasePRNG","@stdlib/buffer/reviver":"reviveBuffer","@stdlib/complex/reviver":"reviveComplex","@stdlib/complex/reviver-float32":"reviveComplex64","@stdlib/complex/reviver-float64":"reviveComplex128","@stdlib/error/reviver":"reviveError","@stdlib/array/reviver":"reviveTypedArray","@stdlib/string/right-pad":"rpad","@stdlib/string/right-trim":"rtrim","@stdlib/utils/safe-int-max":"safeintmax","@stdlib/utils/safe-int-min":"safeintmin","@stdlib/random/sample":"sample","@stdlib/datasets/savoy-stopwords-fin":"SAVOY_STOPWORDS_FIN","@stdlib/datasets/savoy-stopwords-fr":"SAVOY_STOPWORDS_FR","@stdlib/datasets/savoy-stopwords-ger":"SAVOY_STOPWORDS_GER","@stdlib/datasets/savoy-stopwords-it":"SAVOY_STOPWORDS_IT","@stdlib/datasets/savoy-stopwords-por":"SAVOY_STOPWORDS_POR","@stdlib/datasets/savoy-stopwords-sp":"SAVOY_STOPWORDS_SP","@stdlib/datasets/savoy-stopwords-swe":"SAVOY_STOPWORDS_SWE","@stdlib/constants/time/seconds-in-day":"SECONDS_IN_DAY","@stdlib/constants/time/seconds-in-hour":"SECONDS_IN_HOUR","@stdlib/constants/time/seconds-in-minute":"SECONDS_IN_MINUTE","@stdlib/constants/time/seconds-in-week":"SECONDS_IN_WEEK","@stdlib/time/seconds-in-month":"secondsInMonth","@stdlib/time/seconds-in-year":"secondsInYear","@stdlib/utils/define-nonenumerable-property":"setNonEnumerableProperty","@stdlib/utils/define-nonenumerable-read-only-property":"setNonEnumerableReadOnly","@stdlib/utils/define-nonenumerable-read-only-accessor":"setNonEnumerableReadOnlyAccessor","@stdlib/utils/define-nonenumerable-read-write-accessor":"setNonEnumerableReadWriteAccessor","@stdlib/utils/define-nonenumerable-write-only-accessor":"setNonEnumerableWriteOnlyAccessor","@stdlib/utils/define-read-only-property":"setReadOnly","@stdlib/utils/define-read-only-accessor":"setReadOnlyAccessor","@stdlib/utils/define-read-write-accessor":"setReadWriteAccessor","@stdlib/utils/define-write-only-accessor":"setWriteOnlyAccessor","@stdlib/array/shared-buffer":"SharedArrayBuffer","@stdlib/utils/shift":"shift","@stdlib/random/shuffle":"shuffle","@stdlib/utils/size-of":"sizeOf","@stdlib/utils/some":"some","@stdlib/utils/some-by":"someBy","@stdlib/utils/async/some-by":"someByAsync","@stdlib/utils/some-by-right":"someByRight","@stdlib/utils/async/some-by-right":"someByRightAsync","@stdlib/datasets/sotu":"SOTU","@stdlib/datasets/spache-revised":"SPACHE_REVISED","@stdlib/datasets/spam-assassin":"SPAM_ASSASSIN","@stdlib/plot/sparklines/base/ctor":"SparklineBase","@stdlib/array/to-sparse-iterator":"sparsearray2iterator","@stdlib/array/to-sparse-iterator-right":"sparsearray2iteratorRight","@stdlib/streams/node/split":"splitStream","@stdlib/constants/math/float64-sqrt-eps":"SQRT_EPS","@stdlib/constants/math/float64-sqrt-half":"SQRT_HALF","@stdlib/constants/math/float64-sqrt-half-pi":"SQRT_HALF_PI","@stdlib/constants/math/float64-sqrt-phi":"SQRT_PHI","@stdlib/constants/math/float64-sqrt-pi":"SQRT_PI","@stdlib/constants/math/float64-sqrt-three":"SQRT_THREE","@stdlib/constants/math/float64-sqrt-two":"SQRT_TWO","@stdlib/constants/math/float64-sqrt-two-pi":"SQRT_TWO_PI","@stdlib/utils/stack":"Stack","@stdlib/string/startcase":"startcase","@stdlib/string/starts-with":"startsWith","@stdlib/datasets/stopwords-en":"STOPWORDS_EN","@stdlib/array/to-strided-iterator":"stridedarray2iterator","@stdlib/streams/node/from-strided-array":"stridedArrayStream","@stdlib/buffer/from-string":"string2buffer","@stdlib/ndarray/sub2ind":"sub2ind","@stdlib/datasets/suthaharan-multi-hop-sensor-network":"SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","@stdlib/datasets/suthaharan-single-hop-sensor-network":"SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","@stdlib/symbol/ctor":"Symbol","@stdlib/utils/tabulate":"tabulate","@stdlib/utils/tabulate-by":"tabulateBy","@stdlib/utils/async/tabulate-by":"tabulateByAsync","@stdlib/time/tic":"tic","@stdlib/utils/timeit":"timeit","@stdlib/os/tmpdir":"tmpdir","@stdlib/time/toc":"toc","@stdlib/nlp/tokenize":"tokenize","@stdlib/streams/node/transform":"transformStream","@stdlib/string/trim":"trim","@stdlib/utils/try-catch":"trycatch","@stdlib/utils/async/try-catch":"trycatchAsync","@stdlib/utils/try-function":"tryFunction","@stdlib/utils/try-require":"tryRequire","@stdlib/utils/try-then":"trythen","@stdlib/utils/async/try-then":"trythenAsync","@stdlib/stats/ttest":"ttest","@stdlib/stats/ttest2":"ttest2","@stdlib/constants/math/float64-two-pi":"TWO_PI","@stdlib/array/typed":"typedarray","@stdlib/array/to-json":"typedarray2json","@stdlib/array/typed-complex-ctors":"typedarrayComplexCtors","@stdlib/array/typed-complex-dtypes":"typedarrayComplexDataTypes","@stdlib/array/typed-ctors":"typedarrayCtors","@stdlib/array/typed-dtypes":"typedarrayDataTypes","@stdlib/array/pool":"typedarraypool","@stdlib/utils/type-max":"typemax","@stdlib/utils/type-min":"typemin","@stdlib/utils/type-of":"typeOf","@stdlib/constants/math/uint8-max":"UINT8_MAX","@stdlib/constants/math/uint8-num-bytes":"UINT8_NUM_BYTES","@stdlib/array/uint8":"Uint8Array","@stdlib/array/uint8c":"Uint8ClampedArray","@stdlib/constants/math/uint16-max":"UINT16_MAX","@stdlib/constants/math/uint16-num-bytes":"UINT16_NUM_BYTES","@stdlib/array/uint16":"Uint16Array","@stdlib/constants/math/uint32-max":"UINT32_MAX","@stdlib/constants/math/uint32-num-bytes":"UINT32_NUM_BYTES","@stdlib/array/uint32":"Uint32Array","@stdlib/process/umask":"umask","@stdlib/string/uncapitalize":"uncapitalize","@stdlib/utils/uncapitalize-keys":"uncapitalizeKeys","@stdlib/utils/uncurry":"uncurry","@stdlib/utils/uncurry-right":"uncurryRight","@stdlib/constants/string/unicode-max":"UNICODE_MAX","@stdlib/constants/string/unicode-max-bmp":"UNICODE_MAX_BMP","@stdlib/plot/sparklines/unicode/column":"UnicodeColumnChartSparkline","@stdlib/plot/sparklines/unicode/line":"UnicodeLineChartSparkline","@stdlib/plot/sparklines/unicode":"UnicodeSparkline","@stdlib/plot/sparklines/unicode/tristate":"UnicodeTristateChartSparkline","@stdlib/plot/sparklines/unicode/up-down":"UnicodeUpDownChartSparkline","@stdlib/plot/sparklines/unicode/win-loss":"UnicodeWinLossChartSparkline","@stdlib/fs/unlink":"unlink","@stdlib/utils/unshift":"unshift","@stdlib/utils/until":"until","@stdlib/utils/async/until":"untilAsync","@stdlib/utils/until-each":"untilEach","@stdlib/utils/until-each-right":"untilEachRight","@stdlib/utils/unzip":"unzip","@stdlib/string/uppercase":"uppercase","@stdlib/utils/uppercase-keys":"uppercaseKeys","@stdlib/datasets/us-states-abbr":"US_STATES_ABBR","@stdlib/datasets/us-states-capitals":"US_STATES_CAPITALS","@stdlib/datasets/us-states-capitals-names":"US_STATES_CAPITALS_NAMES","@stdlib/datasets/us-states-names":"US_STATES_NAMES","@stdlib/datasets/us-states-names-capitals":"US_STATES_NAMES_CAPITALS","@stdlib/string/utf16-to-utf8-array":"utf16ToUTF8Array","@stdlib/stats/vartest":"vartest","@stdlib/utils/async/series-waterfall":"waterfall","@stdlib/utils/async/while":"whileAsync","@stdlib/utils/while-each":"whileEach","@stdlib/utils/while-each-right":"whileEachRight","@stdlib/utils/while":"whilst","@stdlib/utils/writable-properties":"writableProperties","@stdlib/utils/writable-properties-in":"writablePropertiesIn","@stdlib/utils/writable-property-names":"writablePropertyNames","@stdlib/utils/writable-property-names-in":"writablePropertyNamesIn","@stdlib/utils/writable-property-symbols":"writablePropertySymbols","@stdlib/utils/writable-property-symbols-in":"writablePropertySymbolsIn","@stdlib/fs/write-file":"writeFile","@stdlib/utils/zip":"zip","@stdlib/stats/ztest":"ztest","@stdlib/stats/ztest2":"ztest2"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index 18460fb16ccd..76a3a12f2a77 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -1599,6 +1599,7 @@ var db = { "pick": "obj1 = { 'a': 1, 'b': 2 };\nobj2 = pick( obj1, 'b' )\n", "pickBy": "function predicate( key, value ) {\n return ( value > 1 );\n};\nobj1 = { 'a': 1, 'b': 2 };\nobj2 = pickBy( obj1, predicate )\n", "PINF": "PINF\n", + "pkg2alias": "v = pkg2alias( '@stdlib/math/base/special/sin' )\n", "PLATFORM": "PLATFORM\n", "plot": "plot = plot()\n\n// Provide plot data at instantiation:\nx = [[0.10, 0.20, 0.30]];\ny = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n", "Plot": "plot = Plot()\n\n// Provide plot data at instantiation:\nx = [[0.10, 0.20, 0.30]];\ny = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n", diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index d4de6649e415..bf2452366060 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -26,8 +26,8 @@ var db = { "AFINN_96": "\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n", "AFINN_111": "\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n", - "alias2pkg": "\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n aliases\n", - "aliases": "\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n See Also\n --------\n alias2pkg\n", + "alias2pkg": "\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n aliases, pkg2alias\n", + "aliases": "\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n See Also\n --------\n alias2pkg, pkg2alias\n", "allocUnsafe": "\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n", "anova1": "\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n", "ANSCOMBES_QUARTET": "\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n", @@ -1600,6 +1600,7 @@ var db = { "pick": "\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n", "pickBy": "\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n", "PINF": "\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n", + "pkg2alias": "\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n\n See Also\n --------\n alias2pkg, aliases\n", "PLATFORM": "\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n", "plot": "\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n", "Plot": "\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n", From a7d4cbee9df7a25df9027159be2ff7aad770c34c Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 20:25:20 -0700 Subject: [PATCH 050/142] Add utility to return related aliases --- .../@stdlib/namespace/alias2related/README.md | 173 ++ .../alias2related/benchmark/benchmark.js | 52 + .../@stdlib/namespace/alias2related/bin/cli | 66 + .../namespace/alias2related/data/data.csv | 1886 +++++++++++++++++ .../namespace/alias2related/data/data.json | 1 + .../namespace/alias2related/docs/repl.txt | 22 + .../alias2related/docs/types/index.d.ts | 36 + .../alias2related/docs/types/test.ts | 44 + .../namespace/alias2related/docs/usage.txt | 8 + .../namespace/alias2related/etc/cli_opts.json | 15 + .../namespace/alias2related/examples/index.js | 38 + .../namespace/alias2related/lib/index.js | 40 + .../namespace/alias2related/lib/main.js | 54 + .../namespace/alias2related/package.json | 70 + .../namespace/alias2related/scripts/build.js | 97 + .../namespace/alias2related/test/test.cli.js | 184 ++ .../namespace/alias2related/test/test.js | 92 + 17 files changed, 2878 insertions(+) create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/README.md create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/benchmark/benchmark.js create mode 100755 lib/node_modules/@stdlib/namespace/alias2related/bin/cli create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/data/data.csv create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/data/data.json create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/docs/usage.txt create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/etc/cli_opts.json create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/examples/index.js create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/lib/index.js create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/lib/main.js create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/package.json create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/test/test.cli.js create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/test/test.js diff --git a/lib/node_modules/@stdlib/namespace/alias2related/README.md b/lib/node_modules/@stdlib/namespace/alias2related/README.md new file mode 100644 index 000000000000..df2261814901 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/README.md @@ -0,0 +1,173 @@ + + +# alias2related + +> Return aliases related to a specified alias. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var alias2related = require( '@stdlib/namespace/alias2related' ); +``` + +#### alias2related( alias ) + +Returns aliases related to a specified `alias`. + +```javascript +var out = alias2related( 'base.sin' ); +// returns [...] +``` + +If provided an unrecognized `alias`, the function returns `null`. + +```javascript +var out = alias2related( 'unrecognized_alias_beep_boop_bop_bip' ); +// returns null +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2related = require( '@stdlib/namespace/alias2related' ); + +var list; +var len; +var idx; +var v; +var i; + +list = aliases(); +len = list.length; + +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len ); + v = list[ idx ]; + console.log( 'alias: %s. related: %s.', v, alias2related( v ).join( ', ' ) ); +} +``` + +
+ + + + + +* * * + +
+ +## CLI + + + +
+ +### Usage + +```text +Usage: stdlib-alias2related [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```bash +$ stdlib-alias2related 'base.sin' +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/namespace/alias2related/benchmark/benchmark.js b/lib/node_modules/@stdlib/namespace/alias2related/benchmark/benchmark.js new file mode 100644 index 000000000000..e24504d6b75c --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/benchmark/benchmark.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isStringArray = require( '@stdlib/assert/is-string-array' ).primitives; +var aliases = require( '@stdlib/namespace/aliases' ); +var pkg = require( './../package.json' ).name; +var alias2related = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var v; + var i; + + values = aliases(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = alias2related( values[ i%values.length ] ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( v.length > 0 && !isStringArray( v ) ) { + b.fail( 'should return an array of strings' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/namespace/alias2related/bin/cli b/lib/node_modules/@stdlib/namespace/alias2related/bin/cli new file mode 100755 index 000000000000..41c8a7df70a4 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/bin/cli @@ -0,0 +1,66 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var readFileSync = require( '@stdlib/fs/read-file' ).sync; +var CLI = require( '@stdlib/tools/cli' ); +var alias2related = require( './../lib' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var args; + var cli; + var out; + + // Create a command-line interface: + cli = new CLI({ + 'pkg': require( './../package.json' ), + 'options': require( './../etc/cli_opts.json' ), + 'help': readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }) + }); + + // Get any provided command-line arguments: + args = cli.args(); + + // Resolve related aliases... + out = alias2related( args[ 0 ] ); + if ( out ) { + if ( out.length ) { + console.log( out.join( '\n' ) ); // eslint-disable-line no-console + } + } else { + cli.exit( 1 ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv new file mode 100644 index 000000000000..2831bcea0445 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv @@ -0,0 +1,1886 @@ +AFINN_96,"AFINN_111" +AFINN_111,"AFINN_96" +alias2pkg,"aliases,pkg2alias" +aliases,"alias2pkg,pkg2alias" +allocUnsafe,"Buffer,array2buffer,arraybuffer2buffer,copyBuffer,string2buffer" +anova1,"" +ANSCOMBES_QUARTET,"" +any,"anyBy,every,forEach,none,some" +anyBy,"anyByAsync,anyByRight,everyBy,forEach,noneBy,someBy" +anyByAsync,"anyBy,anyByRightAsync,everyByAsync,forEachAsync,noneByAsync,someByAsync" +anyByRight,"anyBy,anyByRightAsync,everyByRight,forEachRight,noneByRight,someByRight" +anyByRightAsync,"anyByAsync,anyByRight,everyByRightAsync,forEachRightAsync,noneByRightAsync,someByRightAsync" +APERY,"" +append,"prepend,push" +ARCH,"PLATFORM" +argumentFunction,"constantFunction,identity" +ARGV,"ENV" +array,"ndarray" +array2buffer,"Buffer,arraybuffer2buffer,copyBuffer,string2buffer" +array2iterator,"iterator2array,circarray2iterator,array2iteratorRight,stridedarray2iterator" +array2iteratorRight,"iterator2array,array2iterator" +ArrayBuffer,"Buffer,Float32Array,Float64Array,Int16Array,Int32Array,Int8Array,SharedArrayBuffer,Uint16Array,Uint32Array,Uint8Array,Uint8ClampedArray" +arraybuffer2buffer,"Buffer,array2buffer,copyBuffer,string2buffer" +arrayCtors,"typedarrayCtors" +arrayDataType,"arrayDataTypes" +arrayDataTypes,"typedarrayDataTypes,ndarrayDataTypes" +arrayMinDataType,"arrayDataTypes,arrayPromotionRules,arraySafeCasts" +arrayNextDataType,"arrayDataType,arrayDataTypes" +arrayPromotionRules,"arrayDataTypes,arraySafeCasts,ndarrayPromotionRules" +arraySafeCasts,"convertArray,convertArraySame,arrayDataTypes,arraySameKindCasts,ndarraySafeCasts" +arraySameKindCasts,"convertArray,convertArraySame,arrayDataTypes,arraySafeCasts,ndarraySameKindCasts" +arrayShape,"ndarray" +arrayStream,"circularArrayStream,iteratorStream,stridedArrayStream" +arrayview2iterator,"iterator2array,array2iterator,stridedarray2iterator,arrayview2iteratorRight" +arrayview2iteratorRight,"iterator2array,array2iteratorRight,stridedarray2iterator,arrayview2iterator" +AsyncIteratorSymbol,"Symbol,IteratorSymbol" +bartlettTest,"vartest" +base.abs,"base.abs2" +base.abs2,"base.abs" 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+IMG_ALLIUM_OREOPHILUM,"IMG_ACANTHUS_MOLLIS" +IMG_BLACK_CANYON,"" +IMG_DUST_BOWL_HOME,"" +IMG_FRENCH_ALPINE_LANDSCAPE,"" +IMG_LOCOMOTION_HOUSE_CAT,"IMG_LOCOMOTION_NUDE_MALE" +IMG_LOCOMOTION_NUDE_MALE,"IMG_LOCOMOTION_HOUSE_CAT" +IMG_MARCH_PASTORAL,"" +IMG_NAGASAKI_BOATS,"" +incrapcorr,"incrmapcorr,incrpcorr,incrpcorr2" +incrcount,"incrmean,incrsum,incrsummary" +incrcovariance,"incrmcovariance,incrpcorr,incrvariance" +incrcovmat,"incrcovariance,incrpcorrmat" +incrcv,"incrmean,incrmcv,incrstdev,incrvmr" +increwmean,"increwvariance,incrmean,incrmmean,incrwmean" +increwstdev,"increwvariance,incrmstdev,incrstdev" +increwvariance,"increwmean,increwstdev,incrvariance,incrmvariance" +incrgmean,"incrhmean,incrmean,incrmgmean,incrsummary" +incrgrubbs,"incrmgrubbs" +incrhmean,"incrgmean,incrmean,incrmhmean,incrsummary" +incrkmeans,"" +incrkurtosis,"incrmean,incrskewness,incrstdev,incrsummary,incrvariance" +incrmaape,"incrmae,incrmape,incrmean,incrmmaape" 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+incrminabs,"incrmaxabs,incrmin,incrmminabs" +incrminmax,"incrmax,incrmin,incrmminmax,incrrange" +incrminmaxabs,"incrmaxabs,incrminabs,incrminmax,incrmminmaxabs" +incrmmaape,"incrmaape,incrmmape,incrmmpe,incrmmean" +incrmmae,"incrmae,incrmme,incrmmean" +incrmmape,"incrmape,incrmmaape,incrmmpe,incrmmean" +incrmmax,"incrmax,incrmmidrange,incrmmin,incrmrange,incrmsummary" +incrmmaxabs,"incrmaxabs,incrmmax,incrmminabs" +incrmmda,"incrmda,incrmmape" +incrmme,"incrme,incrmmae,incrmmean" +incrmmean,"incrmean,incrmsum,incrmstdev,incrmsummary,incrmvariance" +incrmmeanabs,"incrmeanabs,incrmmean,incrmsumabs" +incrmmeanabs2,"incrmeanabs2,incrmmeanabs,incrmsumabs2" +incrmmeanstdev,"incrmeanstdev,incrmmean,incrmmeanvar,incrmstdev" +incrmmeanvar,"incrmeanvar,incrmmean,incrmmeanstdev,incrmvariance" +incrmmidrange,"incrmmean,incrmmax,incrmmin,incrmrange" +incrmmin,"incrmin,incrmmax,incrmmidrange,incrmrange,incrmsummary" +incrmminabs,"incrminabs,incrmmaxabs,incrmmin" +incrmminmax,"incrmax,incrmin,incrmmax,incrminmax,incrmmin,incrmrange" +incrmminmaxabs,"incrminmaxabs,incrmmax,incrmmaxabs,incrmmin,incrmminabs,incrmminmax" +incrmmpe,"incrmmape,incrmme,incrmpe" +incrmmse,"incrmrmse,incrmrss,incrmse" +incrmpcorr,"incrmcovariance,incrmpcorrdist,incrpcorr" +incrmpcorr2,"incrmapcorr,incrmpcorr,incrpcorr2" +incrmpcorrdist,"incrmpcorr,incrpcorrdist" +incrmpe,"incrmape,incrme,incrmmpe" +incrmprod,"incrmsum,incrprod" +incrmrange,"incrmmax,incrmmean,incrmmin,incrmsummary,incrrange" +incrmrmse,"incrmmse,incrmrss,incrrmse" +incrmrss,"incrrss,incrmmse,incrmrmse" +incrmse,"incrmmse,incrrmse,incrrss" +incrmstdev,"incrmmean,incrmsummary,incrmvariance,incrstdev" +incrmsum,"incrmmean,incrmsummary,incrsum" +incrmsumabs,"incrmmeanabs,incrmsum,incrsum,incrsumabs" +incrmsumabs2,"incrmmeanabs2,incrmsumabs,incrsumabs,incrsumabs2" +incrmsummary,"incrmmean,incrmstdev,incrmsum,incrmvariance,incrsummary" +incrmsumprod,"incrmprod,incrmsum,incrsumprod" +incrmvariance,"incrmmean,incrmstdev,incrmsummary,incrvariance" +incrmvmr,"incrmmean,incrmvariance,incrvmr" +incrpcorr,"incrcovariance,incrmpcorr,incrsummary" +incrpcorr2,"incrapcorr,incrmpcorr2,incrpcorr" +incrpcorrdist,"incrcovariance,incrpcorr,incrsummary" +incrpcorrdistmat,"incrpcorrdist,incrpcorrmat" +incrpcorrmat,"incrcovmat,incrpcorr,incrpcorrdistmat" +incrprod,"incrmprod,incrsum,incrsummary" +incrrange,"incrmax,incrmean,incrmin,incrmrange,incrsummary" +incrrmse,"incrmrmse,incrmse,incrrss" +incrrss,"incrmrss,incrmse,incrrmse" +incrskewness,"incrkurtosis,incrmean,incrstdev,incrsummary,incrvariance" +incrspace,"linspace,logspace" +incrstdev,"incrkurtosis,incrmean,incrmstdev,incrskewness,incrsummary,incrvariance" +incrsum,"incrcount,incrmean,incrmsum,incrprod,incrsummary" +incrsumabs,"incrmeanabs,incrmsumabs,incrsum" +incrsumabs2,"incrmeanabs2,incrmsumabs2,incrsumabs" 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+inheritedNonEnumerableProperties,"inheritedEnumerableProperties,inheritedNonEnumerablePropertyNames,inheritedNonEnumerablePropertySymbols,inheritedKeys,nonEnumerableProperties,nonEnumerablePropertiesIn,properties" +inheritedNonEnumerablePropertyNames,"inheritedNonEnumerableProperties,inheritedNonEnumerablePropertySymbols,objectKeys,nonEnumerablePropertyNames,nonEnumerablePropertyNamesIn,nonEnumerablePropertySymbols,propertyNames" +inheritedNonEnumerablePropertySymbols,"inheritedNonEnumerableProperties,inheritedNonEnumerablePropertyNames,nonEnumerableProperties,nonEnumerablePropertyNames,nonEnumerablePropertySymbols,nonEnumerablePropertySymbolsIn,propertySymbols" +inheritedProperties,"properties,propertiesIn,inheritedPropertyNames,inheritedPropertySymbols" +inheritedPropertyDescriptor,"propertyDescriptor,propertyDescriptorIn,inheritedKeys,inheritedPropertyDescriptors,inheritedPropertyNames,inheritedPropertySymbols" +inheritedPropertyDescriptors,"propertyDescriptors,propertyDescriptorsIn,inheritedKeys,inheritedPropertyNames,inheritedPropertySymbols" +inheritedPropertyNames,"inheritedKeys,inheritedPropertyDescriptors,inheritedPropertySymbols,propertyNames,propertyNamesIn" +inheritedPropertySymbols,"inheritedKeys,inheritedPropertyDescriptors,inheritedPropertyNames,propertySymbols,propertySymbolsIn" +inheritedWritableProperties,"inheritedWritablePropertyNames,inheritedWritablePropertySymbols,writableProperties,writablePropertiesIn,properties" +inheritedWritablePropertyNames,"inheritedWritablePropertySymbols,writablePropertyNames,writablePropertyNamesIn,properties" +inheritedWritablePropertySymbols,"inheritedWritablePropertyNames,writablePropertySymbols,writablePropertySymbolsIn,properties" +inmap,"forEach,inmapRight" +inmapAsync,"forEachAsync,inmapRightAsync,inmap" +inmapRight,"forEachRight,inmap" +inmapRightAsync,"forEachRightAsync,inmapAsync,inmapRight" +inspectSinkStream,"debugSinkStream,inspectStream" +inspectStream,"debugStream" +instanceOf,"isPrototypeOf,constructorName,inherit,typeOf" +INT8_MAX,"INT8_MIN" +INT8_MIN,"INT8_MAX" +INT8_NUM_BYTES,"INT16_NUM_BYTES,INT32_NUM_BYTES,UINT8_NUM_BYTES" +Int8Array,"ArrayBuffer,Float32Array,Float64Array,Int16Array,Int32Array,Uint16Array,Uint32Array,Uint8Array,Uint8ClampedArray" +INT16_MAX,"INT16_MIN" +INT16_MIN,"INT16_MAX" +INT16_NUM_BYTES,"INT32_NUM_BYTES,INT8_NUM_BYTES,UINT16_NUM_BYTES" +Int16Array,"ArrayBuffer,Float32Array,Float64Array,Int32Array,Int8Array,Uint16Array,Uint32Array,Uint8Array,Uint8ClampedArray" +INT32_MAX,"INT32_MIN" +INT32_MIN,"INT32_MAX" +INT32_NUM_BYTES,"INT16_NUM_BYTES,INT8_NUM_BYTES,UINT32_NUM_BYTES" +Int32Array,"ArrayBuffer,Float32Array,Float64Array,Int16Array,Int8Array,Uint16Array,Uint32Array,Uint8Array,Uint8ClampedArray" +IS_BIG_ENDIAN,"IS_LITTLE_ENDIAN" +IS_BROWSER,"" +IS_DARWIN,"" +IS_ELECTRON,"IS_ELECTRON_MAIN,IS_ELECTRON_RENDERER" +IS_ELECTRON_MAIN,"IS_ELECTRON,IS_ELECTRON_RENDERER" +IS_ELECTRON_RENDERER,"IS_ELECTRON,IS_ELECTRON_MAIN" +IS_LITTLE_ENDIAN,"IS_BIG_ENDIAN" +IS_NODE,"" +IS_WEB_WORKER,"" +IS_WINDOWS,"" +isAbsolutePath,"isRelativePath" +isAccessorProperty,"hasOwnProp,isAccessorPropertyIn,isDataProperty" +isAccessorPropertyIn,"hasProp,isAccessorProperty,isDataPropertyIn" +isAlphagram,"isAnagram" +isAlphaNumeric,"isDigitString" +isAnagram,"isAlphagram" +isArguments,"" +isArray,"isArrayLike" +isArrayArray,"" +isArrayBuffer,"isSharedArrayBuffer,isTypedArray" +isArrayLength,"isArray" +isArrayLike,"isArray,isArrayLikeObject" +isArrayLikeObject,"isArray,isArrayLike" +isASCII,"isString" +isBetween,"isBetweenArray" +isBetweenArray,"isBetween" +isBinaryString,"isString" +isBoolean,"" +isBooleanArray,"" +isBoxedPrimitive,"isPrimitive" +isBuffer,"" +isCapitalized,"isString" +isCentrosymmetricMatrix,"isMatrixLike,isSquareMatrix,isSymmetricMatrix" +isCircular,"isCircularArray,isCircularPlainObject" +isCircularArray,"isCircular,isCircularPlainObject" +isCircularPlainObject,"isCircular,isCircularArray" +isCollection,"isArrayLike" +isComplex,"isComplex64,isComplex128" +isComplex64,"isComplex,isComplex128" +isComplex64Array,"isComplex,isComplex64,isComplex128Array,isComplexTypedArray" +isComplex128,"isComplex,isComplex64" +isComplex128Array,"isComplex,isComplex128,isComplex64Array,isComplexTypedArray" +isComplexLike,"isComplex,isComplex64,isComplex128" +isComplexTypedArray,"isComplex,isComplex64Array,isComplex128Array" +isConfigurableProperty,"isConfigurablePropertyIn,isEnumerableProperty,isReadableProperty,isWritableProperty" +isConfigurablePropertyIn,"isConfigurableProperty,isEnumerablePropertyIn,isReadablePropertyIn,isWritablePropertyIn" +isDataProperty,"hasOwnProp,isAccessorProperty,isDataPropertyIn" +isDataPropertyIn,"hasProp,isAccessorPropertyIn,isDataProperty" +isDateObject,"" +isDigitString,"isHexString,isString" +isEmailAddress,"" +isEmptyArray,"isArray" 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+isInteger,"isNumber" +isIntegerArray,"isArray" +isIterableLike,"isIteratorLike" +isIteratorLike,"isIterableLike" +isJSON,"" +isLeapYear,"" +isLowercase,"isString,isUppercase" +isMatrixLike,"isArray,isArrayLike,isndarrayLike,isTypedArrayLike,isVectorLike" +isMethod,"hasOwnProp,isFunction,isMethodIn" +isMethodIn,"hasProp,isFunction,isMethod" +isNamedTypedTupleLike,"namedtypedtuple" +isnan,"isNumber" +isNaNArray,"isnan" +isNativeFunction,"isFunction" +isndarrayLike,"isArray,isArrayLike,isMatrixLike,isTypedArrayLike,isVectorLike" +isNegativeInteger,"isInteger" +isNegativeIntegerArray,"isArray" +isNegativeNumber,"isNumber" +isNegativeNumberArray,"isArray" +isNegativeZero,"isNumber,isPositiveZero" +isNodeBuiltin,"" +isNodeDuplexStreamLike,"isNodeStreamLike" +isNodeReadableStreamLike,"isNodeStreamLike" +isNodeREPL,"" +isNodeStreamLike,"" +isNodeTransformStreamLike,"isNodeStreamLike" +isNodeWritableStreamLike,"isNodeStreamLike" +isNonConfigurableProperty,"isConfigurableProperty,isEnumerableProperty,isNonConfigurablePropertyIn,isNonEnumerableProperty,isReadableProperty,isWritableProperty" +isNonConfigurablePropertyIn,"isConfigurablePropertyIn,isEnumerablePropertyIn,isNonConfigurableProperty,isNonEnumerablePropertyIn,isReadablePropertyIn,isWritablePropertyIn" +isNonEnumerableProperty,"isConfigurableProperty,isEnumerableProperty,isNonConfigurableProperty,isNonEnumerablePropertyIn,isReadableProperty,isWritableProperty" +isNonEnumerablePropertyIn,"isConfigurablePropertyIn,isEnumerablePropertyIn,isNonConfigurablePropertyIn,isNonEnumerableProperty,isReadablePropertyIn,isWritablePropertyIn" +isNonNegativeInteger,"isInteger" +isNonNegativeIntegerArray,"isArray" +isNonNegativeNumber,"isNumber" +isNonNegativeNumberArray,"isArray" +isNonPositiveInteger,"isInteger" +isNonPositiveIntegerArray,"isArray" +isNonPositiveNumber,"isNumber" +isNonPositiveNumberArray,"isArray" 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+isSkewCentrosymmetricMatrix,"isCentrosymmetricMatrix,isMatrixLike,isSkewSymmetricMatrix" +isSkewPersymmetricMatrix,"isMatrixLike,isPersymmetricMatrix,isSkewSymmetricMatrix" +isSkewSymmetricMatrix,"isMatrixLike,isSkewSymmetricMatrix,isSquareMatrix" +isSquareMatrix,"isMatrixLike,isSymmetricMatrix" +isStrictEqual,"isSameValue" +isString,"" +isStringArray,"isArray,isString" +isSymbol,"" +isSymbolArray,"isArray,isSymbol" +isSymmetricMatrix,"isMatrixLike,isNonSymmetricMatrix,isSquareMatrix" +isSyntaxError,"isError" +isTruthy,"isFalsy" +isTruthyArray,"isFalsyArray,isTruthy" +isTypedArray,"isArray,isTypedArrayLike" +isTypedArrayLength,"isArrayLength,isTypedArray" +isTypedArrayLike,"isTypedArray" +isTypeError,"isError" +isUint8Array,"isTypedArray,isUint16Array,isUint32Array" +isUint8ClampedArray,"isTypedArray,isUint8Array" +isUint16Array,"isTypedArray,isUint32Array,isUint8Array" +isUint32Array,"isTypedArray,isUint16Array,isUint8Array" +isUNCPath,"" +isUndefined,"isNull,isUndefinedOrNull" 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+iterator2arrayview,"iterator2array,arrayview2iterator,iterator2arrayviewRight" +iterator2arrayviewRight,"iterator2array,arrayview2iteratorRight,iterator2arrayview" +iteratorStream,"arrayStream" +IteratorSymbol,"Symbol" +iterawgn,"iterawln,iterawun" +iterawln,"iterawgn,iterawun" +iterawun,"iterawgn,iterawln" +iterBartlettHannPulse,"iterBartlettPulse,iterHannPulse,iterPulse,iterTriangleWave" +iterBartlettPulse,"iterBartlettHannPulse,iterPulse,iterTriangleWave" +iterConcat,"" +iterConstant,"constantFunction" +iterCosineWave,"iterPulse,iterSawtoothWave,iterSineWave,iterSquareWave,iterTriangleWave" +iterCounter,"iterLength" +itercugmean,"itercuhmean,itercumean" +itercuhmean,"itercugmean,itercumean" +itercumax,"itercumidrange,itercumin,itercurange,itermax" +itercumaxabs,"itercumax,itercuminabs,itermaxabs" +itercumean,"itercumidrange,itercusum,itermean" +itercumeanabs,"itercumean,itercumeanabs2,itercusumabs,itermeanabs" +itercumeanabs2,"itercumean,itercumeanabs,itercusumabs2,itermeanabs2" 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+iterTriangleWave,"iterPulse,iterSawtoothWave,iterSineWave,iterSquareWave" +iterUnion,"iterIntersection,iterUnique" +iterUnique,"iterUniqueBy,iterUniqueByHash" +iterUniqueBy,"iterUnique,iterUniqueByHash" +iterUniqueByHash,"iterUnique,iterUniqueBy" +iterUnshift,"iterConcat,iterPush,iterShift" +itervariance,"itermean,iterstdev" +joinStream,"splitStream" +kde2d,"" +keyBy,"forEach" +keyByRight,"forEachRight,keyBy" +keysIn,"objectEntriesIn,objectKeys,objectValuesIn" +kruskalTest,"" +kstest,"" +lda,"" +LinkedList,"DoublyLinkedList,Stack" +linspace,"incrspace,logspace" +LIU_NEGATIVE_OPINION_WORDS_EN,"LIU_POSITIVE_OPINION_WORDS_EN" +LIU_POSITIVE_OPINION_WORDS_EN,"LIU_NEGATIVE_OPINION_WORDS_EN" +LN_HALF,"" +LN_PI,"PI" +LN_SQRT_TWO_PI,"PI" +LN_TWO_PI,"TWO_PI" +LN2,"LN10" +LN10,"LN2" +LOG2E,"E,LOG10E" +LOG10E,"E,LOG2E" +logspace,"incrspace,linspace" +lowercase,"uncapitalize,uppercase" +lowercaseKeys,"uncapitalizeKeys,uppercaseKeys" +lowess,"" +lpad,"pad,rpad" +ltrim,"trim,rtrim" 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+nonEnumerablePropertiesIn,"enumerablePropertiesIn,inheritedNonEnumerableProperties,nonEnumerableProperties,propertiesIn" +nonEnumerablePropertyNames,"objectKeys,inheritedNonEnumerablePropertyNames,nonEnumerablePropertyNamesIn,nonEnumerablePropertySymbols,propertyNames" +nonEnumerablePropertyNamesIn,"keysIn,inheritedNonEnumerablePropertyNames,nonEnumerablePropertyNames,propertyNamesIn" +nonEnumerablePropertySymbols,"enumerablePropertySymbols,inheritedNonEnumerablePropertySymbols,nonEnumerablePropertyNames,nonEnumerablePropertySymbolsIn,propertySymbols" +nonEnumerablePropertySymbolsIn,"enumerablePropertySymbolsIn,inheritedNonEnumerablePropertySymbols,nonEnumerablePropertyNamesIn,nonEnumerablePropertySymbols,propertySymbolsIn" +noop,"" +now,"" +NUM_CPUS,"" +Number,"" +objectEntries,"objectEntriesIn,objectFromEntries,objectKeys,objectValues" +objectEntriesIn,"objectEntries,objectFromEntries,keysIn,objectValuesIn" +objectFromEntries,"objectEntries" +objectInverse,"objectInverseBy" +objectInverseBy,"objectInverse" +objectKeys,"objectEntries,keysIn,objectValues" +objectValues,"objectEntries,objectKeys" +objectValuesIn,"objectEntriesIn,keysIn,objectValues" +omit,"omitBy" +omitBy,"omit" +onlineBinaryClassification,"onlineSGDRegression" +onlineSGDRegression,"onlineBinaryClassification" +openURL,"" +PACE_BOSTON_HOUSE_PRICES,"HARRISON_BOSTON_HOUSE_PRICES,HARRISON_BOSTON_HOUSE_PRICES_CORRECTED" +pad,"lpad,rpad" +papply,"papplyRight" +papplyRight,"papply" +parallel,"" +parseJSON,"" +PATH_DELIMITER,"PATH_DELIMITER_POSIX,PATH_DELIMITER_WIN32" +PATH_DELIMITER_POSIX,"PATH_DELIMITER,PATH_DELIMITER_WIN32" +PATH_DELIMITER_WIN32,"PATH_DELIMITER,PATH_DELIMITER_POSIX" +PATH_SEP,"PATH_SEP_POSIX,PATH_SEP_WIN32" +PATH_SEP_POSIX,"PATH_SEP,PATH_SEP_WIN32" +PATH_SEP_WIN32,"PATH_SEP,PATH_SEP_POSIX" +pcorrtest,"" +percentEncode,"" +PHI,"" +PI,"TWO_PI" +PI_SQUARED,"PI" +pick,"pickBy" +pickBy,"pick" +PINF,"NINF" +pkg2alias,"alias2pkg,aliases" +PLATFORM,"ARCH" +plot,"Plot" +Plot,"plot" +pluck,"deepPluck,pick" +pop,"push,shift,unshift" +prepend,"append,unshift" +properties,"defineProperties,inheritedProperties,propertiesIn,propertyNames,propertySymbols" +propertiesIn,"defineProperties,inheritedProperties,properties,propertyNamesIn,propertySymbolsIn" +propertyDescriptor,"hasOwnProp,defineProperty,propertyDescriptorIn,propertyDescriptors" +propertyDescriptorIn,"hasProp,defineProperty,propertyDescriptor,propertyDescriptorsIn" +propertyDescriptors,"defineProperty,defineProperties,propertyDescriptor,propertyDescriptorsIn,propertyNames,propertySymbols" +propertyDescriptorsIn,"defineProperties,propertyDescriptorIn,propertyDescriptors,propertyNamesIn,propertySymbolsIn" +propertyNames,"objectKeys,nonEnumerablePropertyNames,propertyNamesIn,propertySymbols" +propertyNamesIn,"objectKeys,nonEnumerablePropertyNamesIn,propertyNames,propertySymbolsIn" +propertySymbols,"propertyNames,propertySymbolsIn" +propertySymbolsIn,"propertyNamesIn,propertySymbols" +Proxy,"" 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+random.iterators.improvedZiggurat,"base.random.improvedZiggurat" +random.iterators.invgamma,"base.random.invgamma" +random.iterators.kumaraswamy,"base.random.kumaraswamy" +random.iterators.laplace,"base.random.laplace" +random.iterators.levy,"base.random.levy" +random.iterators.logistic,"base.random.logistic" +random.iterators.lognormal,"base.random.lognormal" +random.iterators.minstd,"base.random.minstd,random.iterators.minstdShuffle,random.iterators.mt19937,random.iterators.randi,random.iterators.randu" +random.iterators.minstdShuffle,"base.random.minstdShuffle,random.iterators.minstd,random.iterators.mt19937,random.iterators.randi,random.iterators.randu" +random.iterators.mt19937,"base.random.mt19937,random.iterators.minstd,random.iterators.minstdShuffle,random.iterators.randi,random.iterators.randu" +random.iterators.negativeBinomial,"base.random.negativeBinomial" +random.iterators.normal,"base.random.normal" +random.iterators.pareto1,"base.random.pareto1" +random.iterators.poisson,"base.random.poisson" +random.iterators.randi,"base.random.randi,random.iterators.randu" +random.iterators.randn,"base.random.randn" +random.iterators.randu,"base.random.randu,random.iterators.randi" +random.iterators.rayleigh,"base.random.rayleigh" +random.iterators.t,"base.random.t" +random.iterators.triangular,"base.random.triangular" +random.iterators.uniform,"base.random.uniform" +random.iterators.weibull,"base.random.weibull" +random.streams.arcsine,"base.random.arcsine,random.iterators.arcsine" +random.streams.bernoulli,"base.random.bernoulli,random.iterators.bernoulli" +random.streams.beta,"base.random.beta,random.iterators.beta" +random.streams.betaprime,"base.random.betaprime,random.iterators.betaprime" +random.streams.binomial,"base.random.binomial,random.iterators.binomial" +random.streams.boxMuller,"base.random.boxMuller,random.iterators.boxMuller,random.streams.improvedZiggurat,random.streams.randn" +random.streams.cauchy,"base.random.cauchy,random.iterators.cauchy" +random.streams.chi,"base.random.chi,random.iterators.chi" +random.streams.chisquare,"base.random.chisquare,random.iterators.chisquare" +random.streams.cosine,"base.random.cosine,random.iterators.cosine" +random.streams.discreteUniform,"base.random.discreteUniform,random.iterators.discreteUniform" +random.streams.erlang,"base.random.erlang,random.iterators.erlang" +random.streams.exponential,"base.random.exponential,random.iterators.exponential" +random.streams.f,"base.random.f,random.iterators.f" +random.streams.gamma,"base.random.gamma,random.iterators.gamma" +random.streams.geometric,"base.random.geometric,random.iterators.geometric" +random.streams.gumbel,"base.random.gumbel,random.iterators.gumbel" +random.streams.improvedZiggurat,"base.random.improvedZiggurat,random.iterators.improvedZiggurat,random.streams.boxMuller,random.streams.randn" +random.streams.invgamma,"base.random.invgamma,random.iterators.invgamma" 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+RE_DIRNAME,"RE_DIRNAME_POSIX,RE_DIRNAME_WINDOWS,dirname" +RE_DIRNAME_POSIX,"RE_DIRNAME,RE_DIRNAME_WINDOWS,dirname" +RE_DIRNAME_WINDOWS,"RE_DIRNAME,RE_DIRNAME_POSIX,dirname" +RE_EOL,"" +RE_EXTENDED_LENGTH_PATH,"" +RE_EXTNAME,"RE_EXTNAME_POSIX,RE_EXTNAME_WINDOWS,extname" +RE_EXTNAME_POSIX,"RE_EXTNAME,RE_EXTNAME_WINDOWS,extname" +RE_EXTNAME_WINDOWS,"RE_EXTNAME,RE_EXTNAME_POSIX,extname" +RE_FILENAME,"RE_FILENAME_POSIX,RE_FILENAME_WINDOWS" +RE_FILENAME_POSIX,"RE_FILENAME,RE_FILENAME_WINDOWS" +RE_FILENAME_WINDOWS,"RE_FILENAME,RE_FILENAME_POSIX" +RE_FUNCTION_NAME,"functionName" +RE_NATIVE_FUNCTION,"RE_FUNCTION_NAME,functionName" +RE_REGEXP,"reFromString" +RE_UNC_PATH,"isUNCPath" +RE_UTF16_SURROGATE_PAIR,"RE_UTF16_UNPAIRED_SURROGATE" +RE_UTF16_UNPAIRED_SURROGATE,"RE_UTF16_SURROGATE_PAIR" +RE_WHITESPACE,"isWhitespace" +readDir,"exists,readFile" +readFile,"exists,readDir,readJSON,writeFile" +readFileList,"" +readJSON,"readFile" +readWASM,"readFile" +real,"imag,reim" +realmax,"realmin,typemax" 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+string2buffer,"Buffer,array2buffer,arraybuffer2buffer,copyBuffer" +sub2ind,"array,ndarray,ind2sub" +SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK,"SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK" +SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK,"SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK" +Symbol,"" +tabulate,"countBy,groupBy,tabulateBy" +tabulateBy,"countBy,groupBy,tabulate" +tabulateByAsync,"countByAsync,groupByAsync,tabulateBy" +tic,"toc" +timeit,"" +tmpdir,"configdir,homedir" +toc,"tic" +tokenize,"" +transformStream,"" +trim,"ltrim,pad,rtrim" +trycatch,"trycatchAsync,trythen" +trycatchAsync,"trycatch,trythenAsync" +tryFunction,"" +tryRequire,"" +trythen,"trycatch,trythenAsync" +trythenAsync,"trycatchAsync,trythen" +ttest,"ttest2" +ttest2,"ttest" +TWO_PI,"PI" +typedarray,"Float64Array,Float32Array,Int32Array,Uint32Array,Int16Array,Uint16Array,Int8Array,Uint8Array,Uint8ClampedArray" +typedarray2json,"reviveTypedArray" +typedarrayComplexCtors,"arrayCtors,typedarrayCtors" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/alias2related/docs/repl.txt b/lib/node_modules/@stdlib/namespace/alias2related/docs/repl.txt new file mode 100644 index 000000000000..90204c71a4e6 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/docs/repl.txt @@ -0,0 +1,22 @@ + +{{alias}}( alias ) + Returns aliases related to a specified alias. + + Parameters + ---------- + alias: string + Alias. + + Returns + ------- + out: Array|null + Related aliases. + + Examples + -------- + > var v = {{alias}}( '{{alias:@stdlib/math/base/special/sin}}' ) + [...] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/namespace/alias2related/docs/types/index.d.ts b/lib/node_modules/@stdlib/namespace/alias2related/docs/types/index.d.ts new file mode 100644 index 000000000000..b318721fe068 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/docs/types/index.d.ts @@ -0,0 +1,36 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Returns aliases related to a specified alias. +* +* @param alias - alias +* @returns related aliases +* +* @example +* var out = alias2related( 'base.sin' ); +* // returns [...] +*/ +declare function alias2related( alias: string ): Array | null; + + +// EXPORTS // + +export = alias2related; diff --git a/lib/node_modules/@stdlib/namespace/alias2related/docs/types/test.ts b/lib/node_modules/@stdlib/namespace/alias2related/docs/types/test.ts new file mode 100644 index 000000000000..65b173c9416c --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import alias2related = require( './index' ); + + +// TESTS // + +// The function returns an array of strings or null... +{ + alias2related( 'base.sin' ); // $ExpectType string[] | null +} + +// The compiler throws an error if the function is not provided a string... +{ + alias2related( 5 ); // $ExpectError + alias2related( true ); // $ExpectError + alias2related( false ); // $ExpectError + alias2related( null ); // $ExpectError + alias2related( undefined ); // $ExpectError + alias2related( [] ); // $ExpectError + alias2related( {} ); // $ExpectError + alias2related( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + alias2related( 'base.sin', 'beep' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/namespace/alias2related/docs/usage.txt b/lib/node_modules/@stdlib/namespace/alias2related/docs/usage.txt new file mode 100644 index 000000000000..2cc2f8f19c0a --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/docs/usage.txt @@ -0,0 +1,8 @@ + +Usage: stdlib-alias2related [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. + diff --git a/lib/node_modules/@stdlib/namespace/alias2related/etc/cli_opts.json b/lib/node_modules/@stdlib/namespace/alias2related/etc/cli_opts.json new file mode 100644 index 000000000000..92119c456962 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/etc/cli_opts.json @@ -0,0 +1,15 @@ +{ + "string": [], + "boolean": [ + "help", + "version" + ], + "alias": { + "help": [ + "h" + ], + "version": [ + "V" + ] + } +} diff --git a/lib/node_modules/@stdlib/namespace/alias2related/examples/index.js b/lib/node_modules/@stdlib/namespace/alias2related/examples/index.js new file mode 100644 index 000000000000..6acc28e9240c --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2related = require( './../lib' ); + +var list; +var len; +var idx; +var v; +var i; + +list = aliases(); +len = list.length; + +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len ); + v = list[ idx ]; + console.log( 'alias: %s. related: %s.', v, alias2related( v ).join( ', ' ) ); +} diff --git a/lib/node_modules/@stdlib/namespace/alias2related/lib/index.js b/lib/node_modules/@stdlib/namespace/alias2related/lib/index.js new file mode 100644 index 000000000000..6fefbc7ad257 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return aliases related to a specified alias. +* +* @module @stdlib/namespace/alias2related +* +* @example +* var alias2related = require( '@stdlib/namespace/alias2related' ); +* +* var v = alias2related( 'base.sin' ); +* // returns [...] +*/ + +// MODULES // + +var alias2related = require( './main.js' ); + + +// EXPORTS // + +module.exports = alias2related; diff --git a/lib/node_modules/@stdlib/namespace/alias2related/lib/main.js b/lib/node_modules/@stdlib/namespace/alias2related/lib/main.js new file mode 100644 index 000000000000..0e7197ef0d30 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/lib/main.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var ALIAS_TO_RELATED = require( './../data/data.json' ); + + +// MAIN // + +/** +* Returns aliases related to a specified alias. +* +* @param {string} alias - alias +* @throws {TypeError} must provide a string +* @returns {(StringArray|null)} related aliases +* +* @example +* var v = alias2pkg( 'base.sin' ); +* // returns [...] +*/ +function alias2pkg( alias ) { + if ( !isString( alias ) ) { + throw new TypeError( 'invalid argument. Must provide a string. Value: `' + alias + '`.' ); + } + if ( hasOwnProp( ALIAS_TO_RELATED, alias ) ) { + return ALIAS_TO_RELATED[ alias ].slice(); + } + return null; +} + + +// EXPORTS // + +module.exports = alias2pkg; diff --git a/lib/node_modules/@stdlib/namespace/alias2related/package.json b/lib/node_modules/@stdlib/namespace/alias2related/package.json new file mode 100644 index 000000000000..6537540fd11b --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/namespace/alias2related", + "version": "0.0.0", + "description": "Return aliases related to a specified alias.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "bin": { + "stdlib-alias2related": "./bin/cli" + }, + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "bin": "./bin", + "data": "./data", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "standard", + "library", + "lib", + "aliases", + "alias", + "namespace", + "package", + "name", + "pkg", + "related", + "see", + "also" + ] +} diff --git a/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js b/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js new file mode 100644 index 000000000000..c7137d808289 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var logger = require( 'debug' ); +var writeFile = require( '@stdlib/fs/write-file' ).sync; +var namespace = require( '@stdlib/namespace' ); +var pkg2alias = require( '@stdlib/namespace/pkg2alias' ); +var objectKeys = require( '@stdlib/utils/keys' ); + + +// VARIABLES // + +var debug = logger( 'namespace:alias2related:build' ); + +// Output file paths: +var OUTPUT_JSON = resolve( __dirname, '..', 'data', 'data.json' ); +var OUTPUT_CSV = resolve( __dirname, '..', 'data', 'data.csv' ); + + +// FUNCTIONS // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var related; + var alias; + var fopts; + var keys; + var json; + var csv; + var tmp; + var ns; + var i; + var j; + + debug( 'Extracting namespace alias data...' ); + ns = namespace(); + json = {}; + for ( i = 0; i < ns.length; i++ ) { + related = ns[ i ].related.slice(); + tmp = []; + for ( j = 0; j < related.length; j++ ) { + alias = pkg2alias( related[ j ] ); + if ( alias ) { + tmp.push( alias ); + } else { + console.error( 'WARNING: unable to resolve related alias `'+related[j]+'` for `'+ns[i]+'`.' ); + } + } + json[ ns[i].alias ] = tmp; + } + + debug( 'Writing to JSON file...' ); + fopts = { + 'encoding': 'utf8' + }; + writeFile( OUTPUT_JSON, JSON.stringify( json ), fopts ); + + debug( 'Writing to CSV file...' ); + fopts = { + 'encoding': 'utf8' + }; + keys = objectKeys( json ); + csv = ''; + for ( i = 0; i < keys.length; i++ ) { + csv += keys[ i ] + ',"' + json[ keys[i] ].join( ',' ) + '"\n'; // Note: ensures trailing newline + } + writeFile( OUTPUT_CSV, csv, fopts ); +} + + +// MAIN // + +main(); diff --git a/lib/node_modules/@stdlib/namespace/alias2related/test/test.cli.js b/lib/node_modules/@stdlib/namespace/alias2related/test/test.cli.js new file mode 100644 index 000000000000..17d69a7fc701 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/test/test.cli.js @@ -0,0 +1,184 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var exec = require( 'child_process' ).exec; +var tape = require( 'tape' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); +var readFileSync = require( '@stdlib/fs/read-file' ).sync; + + +// VARIABLES // + +var fpath = resolve( __dirname, '..', 'bin', 'cli' ); +var opts = { + 'skip': IS_BROWSER || IS_WINDOWS +}; + + +// FIXTURES // + +var PKG_VERSION = require( './../package.json' ).version; + + +// TESTS // + +tape( 'command-line interface', function test( t ) { + t.ok( true, __filename ); + t.end(); +}); + +tape( 'when invoked with a `--help` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '--help' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-h` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '-h' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `--version` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '--version' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-V` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '-V' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'the command-line interface prints related aliases', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + 'base.sin' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + stdout = stdout.toString().split( '\n' ); + + // Greater than 1 in order to include the trailing newline: + t.strictEqual( stdout.length > 1, true, 'prints related aliases' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + } + t.end(); + } +}); + +tape( 'if unable to resolve a package name, the command-line interface sets a non-zero exit code', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + 'fjaldfjadljfeoejreandfljasdfjadsfjs' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.pass( error.message ); + t.strictEqual( error.code, 1, 'expected exit code' ); + } + t.strictEqual( stdout.toString(), '', 'does not print to` stdout`' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + t.end(); + } +}); diff --git a/lib/node_modules/@stdlib/namespace/alias2related/test/test.js b/lib/node_modules/@stdlib/namespace/alias2related/test/test.js new file mode 100644 index 000000000000..d8d6ec4cec2d --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/test/test.js @@ -0,0 +1,92 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var DATA = require( './../data/data.json' ); +var alias2related = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof alias2related, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a string', function test( t ) { + var values; + var i; + + values = [ + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + alias2related( value ); + }; + } +}); + +tape( 'the function returns related aliases', function test( t ) { + var expected; + var actual; + var list; + var i; + + list = aliases(); + for ( i = 0; i < list.length; i++ ) { + expected = DATA[ list[i] ]; + actual = alias2related( list[i] ); + t.deepEqual( actual, expected, 'returns expected value for '+list[i] ); + } + t.end(); +}); + +tape( 'the function returns `null` if provided an unrecognized alias', function test( t ) { + var values; + var i; + + values = [ + 'adfkaljdfdsafs', + 'adklfadjflajdslfjalsdf', + 'adflkajdlkfjasdlkfjsadlkfjlasdjflsdjfla' + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( alias2related( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); From d6053e3bcc4a6cfd88b1d802f99d7f206738bf8a Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 20:30:11 -0700 Subject: [PATCH 051/142] Remove environment variables and update recipes --- tools/make/lib/docs/repl.mk | 50 ++++++++++++++++--------------------- 1 file changed, 21 insertions(+), 29 deletions(-) diff --git a/tools/make/lib/docs/repl.mk b/tools/make/lib/docs/repl.mk index 3b0c2bb6b802..ceac16f7e0e1 100644 --- a/tools/make/lib/docs/repl.mk +++ b/tools/make/lib/docs/repl.mk @@ -16,31 +16,13 @@ # limitations under the License. #/ -# VARIABLES # - -# Define the path to the executable for generating REPL help docs: -REPL_BUILD_HELP ?= $(SRC_DIR)/@stdlib/repl/help/scripts/build.js - -# Define the path to the executable for aggregating REPL examples: -REPL_BUILD_EXAMPLES ?= $(SRC_DIR)/@stdlib/repl/code-blocks/scripts/build.js - -# Define the path to the executable for aggregating REPL aliases: -REPL_BUILD_ALIASES ?= $(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js - -# Define the path to the executable for mapping REPL aliases to package names: -REPL_BUILD_ALIAS2PKG ?= $(SRC_DIR)/@stdlib/namespace/alias2pkg/scripts/build.js - -# Define the path to the executable for mapping REPL package names to aliases: -REPL_BUILD_PKG2ALIAS ?= $(SRC_DIR)/@stdlib/namespace/pkg2alias/scripts/build.js - - # TARGETS # # Generate REPL docs. # # This target generates REPL documentation. -repl-docs: repl-help repl-examples repl-aliases repl-alias2pkg repl-pkg2alias +repl-docs: repl-help repl-examples repl-aliases repl-alias2pkg repl-pkg2alias repl-alias2related .PHONY: repl-docs @@ -49,8 +31,8 @@ repl-docs: repl-help repl-examples repl-aliases repl-alias2pkg repl-pkg2alias # # This target generates REPL help documentation. -repl-help: $(NODE_MODULES) $(REPL_BUILD_HELP) - $(QUIET) $(NODE) $(REPL_BUILD_HELP) +repl-help: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/repl/help/scripts/build.js" + $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/repl/help/scripts/build.js" .PHONY: repl-help @@ -59,8 +41,8 @@ repl-help: $(NODE_MODULES) $(REPL_BUILD_HELP) # # This target aggregates REPL examples. -repl-examples: $(NODE_MODULES) $(REPL_BUILD_EXAMPLES) - $(QUIET) $(NODE) $(REPL_BUILD_EXAMPLES) +repl-examples: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/repl/code-blocks/scripts/build.js" + $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/repl/code-blocks/scripts/build.js" .PHONY: repl-examples @@ -69,8 +51,8 @@ repl-examples: $(NODE_MODULES) $(REPL_BUILD_EXAMPLES) # # This target aggregates REPL aliases. -repl-aliases: $(NODE_MODULES) $(REPL_BUILD_ALIASES) - $(QUIET) $(NODE) $(REPL_BUILD_ALIASES) +repl-aliases: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js" + $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js" .PHONY: repl-aliases @@ -79,8 +61,8 @@ repl-aliases: $(NODE_MODULES) $(REPL_BUILD_ALIASES) # # This target rebuilds the REPL database. -repl-alias2pkg: $(NODE_MODULES) $(REPL_BUILD_ALIAS2PKG) - $(QUIET) $(NODE) $(REPL_BUILD_ALIAS2PKG) +repl-alias2pkg: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/alias2pkg/scripts/build.js" + $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/namespace/alias2pkg/scripts/build.js" .PHONY: repl-alias2pkg @@ -89,7 +71,17 @@ repl-alias2pkg: $(NODE_MODULES) $(REPL_BUILD_ALIAS2PKG) # # This target rebuilds the REPL database. -repl-pkg2alias: $(NODE_MODULES) $(REPL_BUILD_PKG2ALIAS) - $(QUIET) $(NODE) $(REPL_BUILD_PKG2ALIAS) +repl-pkg2alias: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/pkg2alias/scripts/build.js" + $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/namespace/pkg2alias/scripts/build.js" .PHONY: repl-pkg2alias + + +# Build the mapping between REPL aliases and related aliases. +# +# This target rebuilds the REPL database. + +repl-alias2related: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/alias2related/scripts/build.js" + $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/namespace/alias2related/scripts/build.js" + +.PHONY: repl-alias2related From 2b65a3110773bf4ee0ef6c9938c243c8fbc36b4f Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 20:31:13 -0700 Subject: [PATCH 052/142] Remove quotes --- tools/make/lib/docs/repl.mk | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/tools/make/lib/docs/repl.mk b/tools/make/lib/docs/repl.mk index ceac16f7e0e1..9a1b57da84cc 100644 --- a/tools/make/lib/docs/repl.mk +++ b/tools/make/lib/docs/repl.mk @@ -31,7 +31,7 @@ repl-docs: repl-help repl-examples repl-aliases repl-alias2pkg repl-pkg2alias re # # This target generates REPL help documentation. -repl-help: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/repl/help/scripts/build.js" +repl-help: $(NODE_MODULES) $(SRC_DIR)/@stdlib/repl/help/scripts/build.js $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/repl/help/scripts/build.js" .PHONY: repl-help @@ -41,7 +41,7 @@ repl-help: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/repl/help/scripts/build.js" # # This target aggregates REPL examples. -repl-examples: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/repl/code-blocks/scripts/build.js" +repl-examples: $(NODE_MODULES) $(SRC_DIR)/@stdlib/repl/code-blocks/scripts/build.js $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/repl/code-blocks/scripts/build.js" .PHONY: repl-examples @@ -51,7 +51,7 @@ repl-examples: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/repl/code-blocks/scripts/buil # # This target aggregates REPL aliases. -repl-aliases: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js" +repl-aliases: $(NODE_MODULES) $(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/namespace/aliases/scripts/build.js" .PHONY: repl-aliases @@ -61,7 +61,7 @@ repl-aliases: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/aliases/scripts/buil # # This target rebuilds the REPL database. -repl-alias2pkg: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/alias2pkg/scripts/build.js" +repl-alias2pkg: $(NODE_MODULES) $(SRC_DIR)/@stdlib/namespace/alias2pkg/scripts/build.js $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/namespace/alias2pkg/scripts/build.js" .PHONY: repl-alias2pkg @@ -71,7 +71,7 @@ repl-alias2pkg: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/alias2pkg/scripts/ # # This target rebuilds the REPL database. -repl-pkg2alias: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/pkg2alias/scripts/build.js" +repl-pkg2alias: $(NODE_MODULES) $(SRC_DIR)/@stdlib/namespace/pkg2alias/scripts/build.js $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/namespace/pkg2alias/scripts/build.js" .PHONY: repl-pkg2alias @@ -81,7 +81,7 @@ repl-pkg2alias: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/pkg2alias/scripts/ # # This target rebuilds the REPL database. -repl-alias2related: $(NODE_MODULES) "$(SRC_DIR)/@stdlib/namespace/alias2related/scripts/build.js" +repl-alias2related: $(NODE_MODULES) $(SRC_DIR)/@stdlib/namespace/alias2related/scripts/build.js $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/namespace/alias2related/scripts/build.js" .PHONY: repl-alias2related From 02bcbf774c7416e79a399ee08cbb398ac9e19df5 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 20:33:11 -0700 Subject: [PATCH 053/142] Update namespace --- .../@stdlib/namespace/alias2pkg/data/data.csv | 1 + .../@stdlib/namespace/alias2pkg/data/data.json | 2 +- .../@stdlib/namespace/alias2related/data/data.csv | 5 +++-- .../@stdlib/namespace/alias2related/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.txt | 1 + .../@stdlib/namespace/lib/namespace/a.js | 12 ++++++++++++ .../@stdlib/namespace/pkg2alias/data/data.csv | 1 + .../@stdlib/namespace/pkg2alias/data/data.json | 2 +- lib/node_modules/@stdlib/repl/code-blocks/lib/db.js | 1 + lib/node_modules/@stdlib/repl/help/lib/db.js | 5 +++-- 11 files changed, 26 insertions(+), 8 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index 8e5fbb33c991..e261d2204d47 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1,6 +1,7 @@ AFINN_96,"@stdlib/datasets/afinn-96" AFINN_111,"@stdlib/datasets/afinn-111" alias2pkg,"@stdlib/namespace/alias2pkg" +alias2related,"@stdlib/namespace/alias2related" aliases,"@stdlib/namespace/aliases" allocUnsafe,"@stdlib/buffer/alloc-unsafe" anova1,"@stdlib/stats/anova1" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index 4771e8ebea87..988423840e28 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ -{"AFINN_96":"@stdlib/datasets/afinn-96","AFINN_111":"@stdlib/datasets/afinn-111","alias2pkg":"@stdlib/namespace/alias2pkg","aliases":"@stdlib/namespace/aliases","allocUnsafe":"@stdlib/buffer/alloc-unsafe","anova1":"@stdlib/stats/anova1","ANSCOMBES_QUARTET":"@stdlib/datasets/anscombes-quartet","any":"@stdlib/utils/any","anyBy":"@stdlib/utils/any-by","anyByAsync":"@stdlib/utils/async/any-by","anyByRight":"@stdlib/utils/any-by-right","anyByRightAsync":"@stdlib/utils/async/any-by-right","APERY":"@stdlib/constants/math/float64-apery","append":"@stdlib/utils/append","ARCH":"@stdlib/os/arch","argumentFunction":"@stdlib/utils/argument-function","ARGV":"@stdlib/process/argv","array":"@stdlib/ndarray/array","array2buffer":"@stdlib/buffer/from-array","array2iterator":"@stdlib/array/to-iterator","array2iteratorRight":"@stdlib/array/to-iterator-right","ArrayBuffer":"@stdlib/array/buffer","arraybuffer2buffer":"@stdlib/buffer/from-arraybuffer","arrayCtors":"@stdlib/array/ctors","arrayDataType":"@stdlib/array/dtype","arrayDataTypes":"@stdlib/array/dtypes","arrayMinDataType":"@stdlib/array/min-dtype","arrayNextDataType":"@stdlib/array/next-dtype","arrayPromotionRules":"@stdlib/array/promotion-rules","arraySafeCasts":"@stdlib/array/safe-casts","arraySameKindCasts":"@stdlib/array/same-kind-casts","arrayShape":"@stdlib/array/shape","arrayStream":"@stdlib/streams/node/from-array","arrayview2iterator":"@stdlib/array/to-view-iterator","arrayview2iteratorRight":"@stdlib/array/to-view-iterator-right","AsyncIteratorSymbol":"@stdlib/symbol/async-iterator","bartlettTest":"@stdlib/stats/bartlett-test","base.abs":"@stdlib/math/base/special/abs","base.abs2":"@stdlib/math/base/special/abs2","base.absdiff":"@stdlib/math/base/utils/absolute-difference","base.absInt32":"@stdlib/math/base/special/int32-abs","base.acos":"@stdlib/math/base/special/acos","base.acosh":"@stdlib/math/base/special/acosh","base.acoth":"@stdlib/math/base/special/acoth","base.acovercos":"@stdlib/math/base/special/acovercos","base.acoversin":"@stdlib/math/base/special/acoversin","base.ahavercos":"@stdlib/math/base/special/ahavercos","base.ahaversin":"@stdlib/math/base/special/ahaversin","base.asin":"@stdlib/math/base/special/asin","base.asinh":"@stdlib/math/base/special/asinh","base.atan":"@stdlib/math/base/special/atan","base.atan2":"@stdlib/math/base/special/atan2","base.atanh":"@stdlib/math/base/special/atanh","base.avercos":"@stdlib/math/base/special/avercos","base.aversin":"@stdlib/math/base/special/aversin","base.bernoulli":"@stdlib/math/base/special/bernoulli","base.besselj0":"@stdlib/math/base/special/besselj0","base.besselj1":"@stdlib/math/base/special/besselj1","base.bessely0":"@stdlib/math/base/special/bessely0","base.bessely1":"@stdlib/math/base/special/bessely1","base.beta":"@stdlib/math/base/special/beta","base.betainc":"@stdlib/math/base/special/betainc","base.betaincinv":"@stdlib/math/base/special/betaincinv","base.betaln":"@stdlib/math/base/special/betaln","base.binet":"@stdlib/math/base/special/binet","base.binomcoef":"@stdlib/math/base/special/binomcoef","base.binomcoefln":"@stdlib/math/base/special/binomcoefln","base.boxcox":"@stdlib/math/base/special/boxcox","base.boxcox1p":"@stdlib/math/base/special/boxcox1p","base.boxcox1pinv":"@stdlib/math/base/special/boxcox1pinv","base.boxcoxinv":"@stdlib/math/base/special/boxcoxinv","base.cabs":"@stdlib/math/base/complex/abs","base.cabs2":"@stdlib/math/base/complex/abs2","base.cadd":"@stdlib/math/base/complex/add","base.cbrt":"@stdlib/math/base/special/cbrt","base.cceil":"@stdlib/math/base/complex/ceil","base.cceiln":"@stdlib/math/base/complex/ceiln","base.ccis":"@stdlib/math/base/complex/cis","base.cdiv":"@stdlib/math/base/complex/divide","base.ceil":"@stdlib/math/base/special/ceil","base.ceil2":"@stdlib/math/base/special/ceil2","base.ceil10":"@stdlib/math/base/special/ceil10","base.ceilb":"@stdlib/math/base/special/ceilb","base.ceiln":"@stdlib/math/base/special/ceiln","base.ceilsd":"@stdlib/math/base/special/ceilsd","base.cexp":"@stdlib/math/base/complex/exp","base.cflipsign":"@stdlib/math/base/complex/flipsign","base.cfloor":"@stdlib/math/base/complex/floor","base.cfloorn":"@stdlib/math/base/complex/floorn","base.cinv":"@stdlib/math/base/complex/inv","base.clamp":"@stdlib/math/base/special/clamp","base.cmul":"@stdlib/math/base/complex/multiply","base.cneg":"@stdlib/math/base/complex/negate","base.continuedFraction":"@stdlib/math/base/tools/continued-fraction","base.copysign":"@stdlib/math/base/special/copysign","base.cos":"@stdlib/math/base/special/cos","base.cosh":"@stdlib/math/base/special/cosh","base.cosm1":"@stdlib/math/base/special/cosm1","base.cospi":"@stdlib/math/base/special/cospi","base.covercos":"@stdlib/math/base/special/covercos","base.coversin":"@stdlib/math/base/special/coversin","base.cphase":"@stdlib/math/base/complex/phase","base.cpolar":"@stdlib/math/base/complex/polar","base.cround":"@stdlib/math/base/complex/round","base.croundn":"@stdlib/math/base/complex/roundn","base.csignum":"@stdli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andom.boxMuller":"@stdlib/random/base/box-muller","base.random.cauchy":"@stdlib/random/base/cauchy","base.random.chi":"@stdlib/random/base/chi","base.random.chisquare":"@stdlib/random/base/chisquare","base.random.cosine":"@stdlib/random/base/cosine","base.random.discreteUniform":"@stdlib/random/base/discrete-uniform","base.random.erlang":"@stdlib/random/base/erlang","base.random.exponential":"@stdlib/random/base/exponential","base.random.f":"@stdlib/random/base/f","base.random.frechet":"@stdlib/random/base/frechet","base.random.gamma":"@stdlib/random/base/gamma","base.random.geometric":"@stdlib/random/base/geometric","base.random.gumbel":"@stdlib/random/base/gumbel","base.random.hypergeometric":"@stdlib/random/base/hypergeometric","base.random.improvedZiggurat":"@stdlib/random/base/improved-ziggurat","base.random.invgamma":"@stdlib/random/base/invgamma","base.random.kumaraswamy":"@stdlib/random/base/kumaraswamy","base.random.laplace":"@stdlib/random/base/laplace","base.random.levy":"@stdlib/random/base/levy","base.random.logistic":"@stdlib/random/base/logistic","base.random.lognormal":"@stdlib/random/base/lognormal","base.random.minstd":"@stdlib/random/base/minstd","base.random.minstdShuffle":"@stdlib/random/base/minstd-shuffle","base.random.mt19937":"@stdlib/random/base/mt19937","base.random.negativeBinomial":"@stdlib/random/base/negative-binomial","base.random.normal":"@stdlib/random/base/normal","base.random.pareto1":"@stdlib/random/base/pareto-type1","base.random.poisson":"@stdlib/random/base/poisson","base.random.randi":"@stdlib/random/base/randi","base.random.randn":"@stdlib/random/base/randn","base.random.randu":"@stdlib/random/base/randu","base.random.rayleigh":"@stdlib/random/base/rayleigh","base.random.t":"@stdlib/random/base/t","base.random.triangular":"@stdlib/random/base/triangular","base.random.uniform":"@stdlib/random/base/uniform","base.random.weibull":"@stdlib/random/base/weibull","base.reldiff":"@stdlib/math/base/utils/relative-difference","base.rempio2":"@stdlib/math/base/special/rempio2","base.risingFactorial":"@stdlib/math/base/special/rising-factorial","base.rotl32":"@stdlib/number/uint32/base/rotl","base.rotr32":"@stdlib/number/uint32/base/rotr","base.round":"@stdlib/math/base/special/round","base.round2":"@stdlib/math/base/special/round2","base.round10":"@stdlib/math/base/special/round10","base.roundb":"@stdlib/math/base/special/roundb","base.roundn":"@stdlib/math/base/special/roundn","base.roundsd":"@stdlib/math/base/special/roundsd","base.rsqrt":"@stdlib/math/base/special/rsqrt","base.sasum":"@stdlib/blas/base/sasum","base.saxpy":"@stdlib/blas/base/saxpy","base.scopy":"@stdlib/blas/base/scopy","base.setHighWord":"@stdlib/number/float64/base/set-high-word","base.setLowWord":"@stdlib/number/float64/base/set-low-word","base.sici":"@stdlib/math/base/special/sici","base.signbit":"@stdlib/number/float64/base/signbit","base.signbitf":"@stdlib/number/float32/base/signbit","base.significandf":"@stdlib/number/float32/base/significand","base.signum":"@stdlib/math/base/special/signum","base.sin":"@stdlib/math/base/special/sin","base.sinc":"@stdlib/math/base/special/sinc","base.sincos":"@stdlib/math/base/special/sincos","base.sincospi":"@stdlib/math/base/special/sincospi","base.sinh":"@stdlib/math/base/special/sinh","base.sinpi":"@stdlib/math/base/special/sinpi","base.spence":"@stdlib/math/base/special/spence","base.sqrt":"@stdlib/math/base/special/sqrt","base.sqrt1pm1":"@stdlib/math/base/special/sqrt1pm1","base.sumSeries":"@stdlib/math/base/tools/sum-series","base.tan":"@stdlib/math/base/special/tan","base.tanh":"@stdlib/math/base/special/tanh","base.toBinaryString":"@stdlib/number/float64/base/to-binary-string","base.toBinaryStringf":"@stdlib/number/float32/base/to-binary-string","base.toBinaryStringUint8":"@stdlib/number/uint8/base/to-binary-string","base.toBinaryStringUint16":"@stdlib/number/uint16/base/to-binary-string","base.toBinaryStringUint32":"@stdlib/number/uint32/base/to-binary-string","base.toWordf":"@stdlib/number/float32/base/to-word","base.toWords":"@stdlib/number/float64/base/to-words","base.trigamma":"@stdlib/math/base/special/trigamma","base.trunc":"@stdlib/math/base/special/trunc","base.trunc2":"@stdlib/math/base/special/trunc2","base.trunc10":"@stdlib/math/base/special/trunc10","base.truncb":"@stdlib/math/base/special/truncb","base.truncn":"@stdlib/math/base/special/truncn","base.truncsd":"@stdlib/math/base/special/truncsd","base.uimul":"@stdlib/math/base/special/uimul","base.uimuldw":"@stdlib/math/base/special/uimuldw","base.uint32ToInt32":"@stdlib/number/uint32/base/to-int32","base.vercos":"@stdlib/math/base/special/vercos","base.versin":"@stdlib/math/base/special/versin","base.wrap":"@stdlib/math/base/special/wrap","base.xlog1py":"@stdlib/math/base/special/xlog1py","base.xlogy":"@stdlib/math/base/special/xlogy","base.zeta":"@stdlib/math/base/special/riemann-zeta","BERNDT_CPS_WAGES_1985":"@stdlib/datasets/berndt-cps-wages-1985","bifurcate":"@stdlib/utils/bifurcate","bifur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araswamy/variance","base.dists.laplace.cdf":"@stdlib/stats/base/dists/laplace/cdf","base.dists.laplace.entropy":"@stdlib/stats/base/dists/laplace/entropy","base.dists.laplace.kurtosis":"@stdlib/stats/base/dists/laplace/kurtosis","base.dists.laplace.Laplace":"@stdlib/stats/base/dists/laplace/ctor","base.dists.laplace.logcdf":"@stdlib/stats/base/dists/laplace/logcdf","base.dists.laplace.logpdf":"@stdlib/stats/base/dists/laplace/logpdf","base.dists.laplace.mean":"@stdlib/stats/base/dists/laplace/mean","base.dists.laplace.median":"@stdlib/stats/base/dists/laplace/median","base.dists.laplace.mgf":"@stdlib/stats/base/dists/laplace/mgf","base.dists.laplace.mode":"@stdlib/stats/base/dists/laplace/mode","base.dists.laplace.pdf":"@stdlib/stats/base/dists/laplace/pdf","base.dists.laplace.quantile":"@stdlib/stats/base/dists/laplace/quantile","base.dists.laplace.skewness":"@stdlib/stats/base/dists/laplace/skewness","base.dists.laplace.stdev":"@stdlib/stats/base/dists/laplace/stdev","base.dists.laplace.variance":"@stdlib/stats/base/dists/laplace/variance","base.dists.levy.cdf":"@stdlib/stats/base/dists/levy/cdf","base.dists.levy.entropy":"@stdlib/stats/base/dists/levy/entropy","base.dists.levy.Levy":"@stdlib/stats/base/dists/levy/ctor","base.dists.levy.logcdf":"@stdlib/stats/base/dists/levy/logcdf","base.dists.levy.logpdf":"@stdlib/stats/base/dists/levy/logpdf","base.dists.levy.mean":"@stdlib/stats/base/dists/levy/mean","base.dists.levy.median":"@stdlib/stats/base/dists/levy/median","base.dists.levy.mode":"@stdlib/stats/base/dists/levy/mode","base.dists.levy.pdf":"@stdlib/stats/base/dists/levy/pdf","base.dists.levy.quantile":"@stdlib/stats/base/dists/levy/quantile","base.dists.levy.stdev":"@stdlib/stats/base/dists/levy/stdev","base.dists.levy.variance":"@stdlib/stats/base/dists/levy/variance","base.dists.logistic.cdf":"@stdlib/stats/base/dists/logistic/cdf","base.dists.logistic.entropy":"@stdlib/stats/base/dists/logistic/entropy","base.dists.logistic.kurtosis":"@stdlib/stats/base/dists/logistic/kurtosis","base.dists.logistic.logcdf":"@stdlib/stats/base/dists/logistic/logcdf","base.dists.logistic.Logistic":"@stdlib/stats/base/dists/logistic/ctor","base.dists.logistic.logpdf":"@stdlib/stats/base/dists/logistic/logpdf","base.dists.logistic.mean":"@stdlib/stats/base/dists/logistic/mean","base.dists.logistic.median":"@stdlib/stats/base/dists/logistic/median","base.dists.logistic.mgf":"@stdlib/stats/base/dists/logistic/mgf","base.dists.logistic.mode":"@stdlib/stats/base/dists/logistic/mode","base.dists.logistic.pdf":"@stdlib/stats/base/dists/logistic/pdf","base.dists.logistic.quantile":"@stdlib/stats/base/dists/logistic/quantile","base.dists.logistic.skewness":"@stdlib/stats/base/dists/logistic/skewness","base.dists.logistic.stdev":"@stdlib/stats/base/dists/logistic/stdev","base.dists.logistic.variance":"@stdlib/stats/base/dists/logistic/variance","base.dists.lognormal.cdf":"@stdlib/stats/base/dists/lognormal/cdf","base.dists.lognormal.entropy":"@stdlib/stats/base/dists/lognormal/entropy","base.dists.lognormal.kurtosis":"@stdlib/stats/base/dists/lognormal/kurtosis","base.dists.lognormal.LogNormal":"@stdlib/stats/base/dists/lognormal/ctor","base.dists.lognormal.logpdf":"@stdlib/stats/base/dists/lognormal/logpdf","base.dists.lognormal.mean":"@stdlib/stats/base/dists/lognormal/mean","base.dists.lognormal.median":"@stdlib/stats/base/dists/lognormal/median","base.dists.lognormal.mode":"@stdlib/stats/base/dists/lognormal/mode","base.dists.lognormal.pdf":"@stdlib/stats/base/dists/lognormal/pdf","base.dists.lognormal.quantile":"@stdlib/stats/base/dists/lognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdli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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv index 2831bcea0445..3b6a1dea672f 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv @@ -1,7 +1,8 @@ AFINN_96,"AFINN_111" AFINN_111,"AFINN_96" -alias2pkg,"aliases,pkg2alias" -aliases,"alias2pkg,pkg2alias" +alias2pkg,"alias2related,aliases,pkg2alias" +alias2related,"alias2pkg,aliases" +aliases,"alias2pkg,alias2related,pkg2alias" allocUnsafe,"Buffer,array2buffer,arraybuffer2buffer,copyBuffer,string2buffer" anova1,"" ANSCOMBES_QUARTET,"" diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.json b/lib/node_modules/@stdlib/namespace/alias2related/data/data.json index c1f05cc3147a..3d3b98b4f7d3 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.json +++ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index cf12cef10de2..353c05d496a2 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1,6 +1,7 @@ AFINN_96 AFINN_111 alias2pkg +alias2related aliases allocUnsafe anova1 diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/a.js b/lib/node_modules/@stdlib/namespace/lib/namespace/a.js index 514538af525e..bd4097905154 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/a.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/a.js @@ -58,6 +58,18 @@ ns.push({ ] }); +ns.push({ + 'alias': 'alias2related', + 'path': '@stdlib/namespace/alias2related', + 'value': require( '@stdlib/namespace/alias2related' ), + 'type': 'Function', + 'related': [ + '@stdlib/namespace/alias2pkg', + '@stdlib/namespace/aliases', + '@stdlib/namespace/pkg2related' + ] +}); + ns.push({ 'alias': 'aliases', 'path': '@stdlib/namespace/aliases', diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index ce94add28746..b69ec4dbb0a7 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -1,6 +1,7 @@ "@stdlib/datasets/afinn-96",AFINN_96 "@stdlib/datasets/afinn-111",AFINN_111 "@stdlib/namespace/alias2pkg",alias2pkg +"@stdlib/namespace/alias2related",alias2related "@stdlib/namespace/aliases",aliases "@stdlib/buffer/alloc-unsafe",allocUnsafe "@stdlib/stats/anova1",anova1 diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index 0856d50f91c2..59249b926353 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ 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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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artcase":"startcase","@stdlib/string/starts-with":"startsWith","@stdlib/datasets/stopwords-en":"STOPWORDS_EN","@stdlib/array/to-strided-iterator":"stridedarray2iterator","@stdlib/streams/node/from-strided-array":"stridedArrayStream","@stdlib/buffer/from-string":"string2buffer","@stdlib/ndarray/sub2ind":"sub2ind","@stdlib/datasets/suthaharan-multi-hop-sensor-network":"SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","@stdlib/datasets/suthaharan-single-hop-sensor-network":"SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","@stdlib/symbol/ctor":"Symbol","@stdlib/utils/tabulate":"tabulate","@stdlib/utils/tabulate-by":"tabulateBy","@stdlib/utils/async/tabulate-by":"tabulateByAsync","@stdlib/time/tic":"tic","@stdlib/utils/timeit":"timeit","@stdlib/os/tmpdir":"tmpdir","@stdlib/time/toc":"toc","@stdlib/nlp/tokenize":"tokenize","@stdlib/streams/node/transform":"transformStream","@stdlib/string/trim":"trim","@stdlib/utils/try-catch":"trycatch","@stdlib/utils/async/try-catch":"trycatchAsync","@stdlib/utils/try-function":"tryFunction","@stdlib/utils/try-require":"tryRequire","@stdlib/utils/try-then":"trythen","@stdlib/utils/async/try-then":"trythenAsync","@stdlib/stats/ttest":"ttest","@stdlib/stats/ttest2":"ttest2","@stdlib/constants/math/float64-two-pi":"TWO_PI","@stdlib/array/typed":"typedarray","@stdlib/array/to-json":"typedarray2json","@stdlib/array/typed-complex-ctors":"typedarrayComplexCtors","@stdlib/array/typed-complex-dtypes":"typedarrayComplexDataTypes","@stdlib/array/typed-ctors":"typedarrayCtors","@stdlib/array/typed-dtypes":"typedarrayDataTypes","@stdlib/array/pool":"typedarraypool","@stdlib/utils/type-max":"typemax","@stdlib/utils/type-min":"typemin","@stdlib/utils/type-of":"typeOf","@stdlib/constants/math/uint8-max":"UINT8_MAX","@stdlib/constants/math/uint8-num-bytes":"UINT8_NUM_BYTES","@stdlib/array/uint8":"Uint8Array","@stdlib/array/uint8c":"Uint8ClampedArray","@stdlib/constants/math/uint16-max":"UINT16_MAX","@stdlib/constants/math/uint16-num-bytes":"UINT16_NUM_BYTES","@stdlib/array/uint16":"Uint16Array","@stdlib/constants/math/uint32-max":"UINT32_MAX","@stdlib/constants/math/uint32-num-bytes":"UINT32_NUM_BYTES","@stdlib/array/uint32":"Uint32Array","@stdlib/process/umask":"umask","@stdlib/string/uncapitalize":"uncapitalize","@stdlib/utils/uncapitalize-keys":"uncapitalizeKeys","@stdlib/utils/uncurry":"uncurry","@stdlib/utils/uncurry-right":"uncurryRight","@stdlib/constants/string/unicode-max":"UNICODE_MAX","@stdlib/constants/string/unicode-max-bmp":"UNICODE_MAX_BMP","@stdlib/plot/sparklines/unicode/column":"UnicodeColumnChartSparkline","@stdlib/plot/sparklines/unicode/line":"UnicodeLineChartSparkline","@stdlib/plot/sparklines/unicode":"UnicodeSparkline","@stdlib/plot/sparklines/unicode/tristate":"UnicodeTristateChartSparkline","@stdlib/plot/sparklines/unicode/up-down":"UnicodeUpDownChartSparkline","@stdlib/plot/sparklines/unicode/win-loss":"UnicodeWinLossChartSparkline","@stdlib/fs/unlink":"unlink","@stdlib/utils/unshift":"unshift","@stdlib/utils/until":"until","@stdlib/utils/async/until":"untilAsync","@stdlib/utils/until-each":"untilEach","@stdlib/utils/until-each-right":"untilEachRight","@stdlib/utils/unzip":"unzip","@stdlib/string/uppercase":"uppercase","@stdlib/utils/uppercase-keys":"uppercaseKeys","@stdlib/datasets/us-states-abbr":"US_STATES_ABBR","@stdlib/datasets/us-states-capitals":"US_STATES_CAPITALS","@stdlib/datasets/us-states-capitals-names":"US_STATES_CAPITALS_NAMES","@stdlib/datasets/us-states-names":"US_STATES_NAMES","@stdlib/datasets/us-states-names-capitals":"US_STATES_NAMES_CAPITALS","@stdlib/string/utf16-to-utf8-array":"utf16ToUTF8Array","@stdlib/stats/vartest":"vartest","@stdlib/utils/async/series-waterfall":"waterfall","@stdlib/utils/async/while":"whileAsync","@stdlib/utils/while-each":"whileEach","@stdlib/utils/while-each-right":"whileEachRight","@stdlib/utils/while":"whilst","@stdlib/utils/writable-properties":"writableProperties","@stdlib/utils/writable-properties-in":"writablePropertiesIn","@stdlib/utils/writable-property-names":"writablePropertyNames","@stdlib/utils/writable-property-names-in":"writablePropertyNamesIn","@stdlib/utils/writable-property-symbols":"writablePropertySymbols","@stdlib/utils/writable-property-symbols-in":"writablePropertySymbolsIn","@stdlib/fs/write-file":"writeFile","@stdlib/utils/zip":"zip","@stdlib/stats/ztest":"ztest","@stdlib/stats/ztest2":"ztest2"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index 76a3a12f2a77..de11f418a01f 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -27,6 +27,7 @@ var db = { "AFINN_96": "list = AFINN_96()\n", "AFINN_111": "list = AFINN_111()\n", "alias2pkg": "v = alias2pkg( 'base.sin' )\n", + "alias2related": "v = alias2related( 'base.sin' )\n", "aliases": "o = aliases()\n", "allocUnsafe": "buf = allocUnsafe( 100 )\n", "anova1": "x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nf = [\n'control', 'treatA', 'treatB', 'treatC', 'control',\n'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n];\nout = anova1( x, f )\n", diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index bf2452366060..51ade4c80780 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -26,8 +26,9 @@ var db = { "AFINN_96": "\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n", "AFINN_111": "\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n", - "alias2pkg": "\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n aliases, pkg2alias\n", - "aliases": "\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n See Also\n --------\n alias2pkg, pkg2alias\n", + "alias2pkg": "\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n", + "alias2related": "\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases\n", + "aliases": "\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n", "allocUnsafe": "\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n", "anova1": "\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n", "ANSCOMBES_QUARTET": "\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n", From 3f75a515cec4618b1d7fa070d9a98f69d7312ec2 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 20:37:19 -0700 Subject: [PATCH 054/142] Fix off-by-one error in examples --- lib/node_modules/@stdlib/namespace/alias2pkg/README.md | 2 +- lib/node_modules/@stdlib/namespace/alias2pkg/examples/index.js | 2 +- lib/node_modules/@stdlib/namespace/alias2related/README.md | 2 +- .../@stdlib/namespace/alias2related/examples/index.js | 2 +- lib/node_modules/@stdlib/namespace/aliases/README.md | 2 +- lib/node_modules/@stdlib/namespace/aliases/examples/index.js | 2 +- lib/node_modules/@stdlib/namespace/pkg2alias/README.md | 2 +- lib/node_modules/@stdlib/namespace/pkg2alias/examples/index.js | 2 +- 8 files changed, 8 insertions(+), 8 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/README.md b/lib/node_modules/@stdlib/namespace/alias2pkg/README.md index 65218b23552e..6b5d8a5fd75f 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/README.md +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/README.md @@ -93,7 +93,7 @@ list = aliases(); len = list.length; for ( i = 0; i < 100; i++ ) { - idx = discreteUniform( 0, len ); + idx = discreteUniform( 0, len-1 ); v = list[ idx ]; console.log( 'alias: %s. pkg: %s.', v, alias2pkg( v ) ); } diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/examples/index.js b/lib/node_modules/@stdlib/namespace/alias2pkg/examples/index.js index bab54d1757d9..5b097c603503 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/examples/index.js +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/examples/index.js @@ -32,7 +32,7 @@ list = aliases(); len = list.length; for ( i = 0; i < 100; i++ ) { - idx = discreteUniform( 0, len ); + idx = discreteUniform( 0, len-1 ); v = list[ idx ]; console.log( 'alias: %s. pkg: %s.', v, alias2pkg( v ) ); } diff --git a/lib/node_modules/@stdlib/namespace/alias2related/README.md b/lib/node_modules/@stdlib/namespace/alias2related/README.md index df2261814901..0e713fc8ceb4 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/README.md +++ b/lib/node_modules/@stdlib/namespace/alias2related/README.md @@ -93,7 +93,7 @@ list = aliases(); len = list.length; for ( i = 0; i < 100; i++ ) { - idx = discreteUniform( 0, len ); + idx = discreteUniform( 0, len-1 ); v = list[ idx ]; console.log( 'alias: %s. related: %s.', v, alias2related( v ).join( ', ' ) ); } diff --git a/lib/node_modules/@stdlib/namespace/alias2related/examples/index.js b/lib/node_modules/@stdlib/namespace/alias2related/examples/index.js index 6acc28e9240c..fc82e93ebef7 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/examples/index.js +++ b/lib/node_modules/@stdlib/namespace/alias2related/examples/index.js @@ -32,7 +32,7 @@ list = aliases(); len = list.length; for ( i = 0; i < 100; i++ ) { - idx = discreteUniform( 0, len ); + idx = discreteUniform( 0, len-1 ); v = list[ idx ]; console.log( 'alias: %s. related: %s.', v, alias2related( v ).join( ', ' ) ); } diff --git a/lib/node_modules/@stdlib/namespace/aliases/README.md b/lib/node_modules/@stdlib/namespace/aliases/README.md index 5083396e5e06..57a959451b61 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/README.md +++ b/lib/node_modules/@stdlib/namespace/aliases/README.md @@ -65,7 +65,7 @@ len = list.length; // Select random aliases from the list... for ( i = 0; i < 100; i++ ) { - idx = discreteUniform( 0, len ); + idx = discreteUniform( 0, len-1 ); console.log( list[ idx ] ); } ``` diff --git a/lib/node_modules/@stdlib/namespace/aliases/examples/index.js b/lib/node_modules/@stdlib/namespace/aliases/examples/index.js index 443c27edad47..2aeaf8ab6f09 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/examples/index.js +++ b/lib/node_modules/@stdlib/namespace/aliases/examples/index.js @@ -31,6 +31,6 @@ len = list.length; // Select random aliases from the list... for ( i = 0; i < 100; i++ ) { - idx = discreteUniform( 0, len ); + idx = discreteUniform( 0, len-1 ); console.log( list[ idx ] ); } diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/README.md b/lib/node_modules/@stdlib/namespace/pkg2alias/README.md index e9fb9be33663..38e68815f974 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/README.md +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/README.md @@ -96,7 +96,7 @@ len = list.length; // Round-trip from alias-to-pkg-to-alias... for ( i = 0; i < 100; i++ ) { - idx = discreteUniform( 0, len ); + idx = discreteUniform( 0, len-1 ); v1 = alias2pkg( list[ idx ] ); v2 = pkg2alias( v1 ); console.log( 'alias: %s. pkg: %s.', list[ idx ], v1 ); diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/examples/index.js b/lib/node_modules/@stdlib/namespace/pkg2alias/examples/index.js index f95ff36c579e..26a8119240c7 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/examples/index.js +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/examples/index.js @@ -35,7 +35,7 @@ len = list.length; // Round-trip from alias-to-pkg-to-alias... for ( i = 0; i < 100; i++ ) { - idx = discreteUniform( 0, len ); + idx = discreteUniform( 0, len-1 ); v1 = alias2pkg( list[ idx ] ); v2 = pkg2alias( v1 ); console.log( 'alias: %s. pkg: %s.', list[ idx ], v1 ); From ba054531ae23de1a21819bb93055c4fe83eaef63 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 20:38:31 -0700 Subject: [PATCH 055/142] Fix off-by-one error --- lib/node_modules/@stdlib/datasets/month-names-en/README.md | 2 +- .../@stdlib/datasets/month-names-en/examples/index.js | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/lib/node_modules/@stdlib/datasets/month-names-en/README.md b/lib/node_modules/@stdlib/datasets/month-names-en/README.md index 7fe33b61816d..18cd8d57ffd3 100644 --- a/lib/node_modules/@stdlib/datasets/month-names-en/README.md +++ b/lib/node_modules/@stdlib/datasets/month-names-en/README.md @@ -80,7 +80,7 @@ len = list.length; // Select random months from the list... for ( i = 0; i < 100; i++ ) { - idx = discreteUniform( 0, len ); + idx = discreteUniform( 0, len-1 ); console.log( list[ idx ] ); } ``` diff --git a/lib/node_modules/@stdlib/datasets/month-names-en/examples/index.js b/lib/node_modules/@stdlib/datasets/month-names-en/examples/index.js index 1daad0627761..a8e29633cb04 100644 --- a/lib/node_modules/@stdlib/datasets/month-names-en/examples/index.js +++ b/lib/node_modules/@stdlib/datasets/month-names-en/examples/index.js @@ -31,6 +31,6 @@ len = list.length; // Select random months from the list... for ( i = 0; i < 100; i++ ) { - idx = discreteUniform( 0, len ); + idx = discreteUniform( 0, len-1 ); console.log( list[ idx ] ); } From 5b9a8fa1e2228e2aa7e333deb2d77cd57ecc2080 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 21:27:15 -0700 Subject: [PATCH 056/142] Add data package files --- .../@stdlib/namespace/alias2pkg/LICENSE | 356 ++++++++++++++++++ .../@stdlib/namespace/alias2pkg/README.md | 14 + .../namespace/alias2pkg/datapackage.json | 56 +++ 3 files changed, 426 insertions(+) create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/LICENSE create mode 100644 lib/node_modules/@stdlib/namespace/alias2pkg/datapackage.json diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/LICENSE b/lib/node_modules/@stdlib/namespace/alias2pkg/LICENSE new file mode 100644 index 000000000000..dc6d53e33997 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/LICENSE @@ -0,0 +1,356 @@ +The use of the database is licensed under an Open Data Commons Public Domain +Dedication & License 1.0 (PDDL 1.0), while the database contents are licensed +under Creative Commons Zero v1.0 Universal (CC0 1.0). 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It replaces any earlier understandings, agreements or representations with respect to the Work not specified here. + +6.3 This Document does not affect any rights that You or anyone else may independently have under any applicable law to make any use of this Work, including (for jurisdictions where this Document is a licence) fair dealing, fair use, database exceptions, or any other legally recognised limitation or exception to infringement of copyright or other applicable laws. + +6.4 This Document takes effect in the relevant jurisdiction in which the Document terms are sought to be enforced. If the rights waived or granted under applicable law in the relevant jurisdiction includes additional rights not waived or granted under this Document, these additional rights are included in this Document in order to meet the intent of this Document. diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/README.md b/lib/node_modules/@stdlib/namespace/alias2pkg/README.md index 6b5d8a5fd75f..ffcfce3d6ed8 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/README.md +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/README.md @@ -165,10 +165,24 @@ $ stdlib-alias2pkg 'base.sin' + + +## License + +The data files (databases) are licensed under an [Open Data Commons Public Domain Dedication & License 1.0][pddl-1.0] and their contents are licensed under [Creative Commons Zero v1.0 Universal][cc0]. The software is licensed under [Apache License, Version 2.0][apache-license]. + + +
+[pddl-1.0]: http://opendatacommons.org/licenses/pddl/1.0/ + +[cc0]: https://creativecommons.org/publicdomain/zero/1.0 + +[apache-license]: https://www.apache.org/licenses/LICENSE-2.0 +
diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/datapackage.json b/lib/node_modules/@stdlib/namespace/alias2pkg/datapackage.json new file mode 100644 index 000000000000..740ee9820ba5 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/datapackage.json @@ -0,0 +1,56 @@ +{ + "name": "stdlib-alias2pkg", + "version": "", + "title": "Standard Library Aliases and Package Names", + "description": "A mapping between standard library aliases and package names.", + "resources": [ + { + "name": "stdlib-alias2pkg-json", + "title": "Standard Library Aliases and Package Names", + "description": "A mapping between standard library aliases and package names.", + "format": "json", + "mediatype": "application/json", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.json" + }, + { + "name": "stdlib-alias2pkg-csv", + "title": "Standard Library Aliases and Package Names", + "description": "A mapping between standard library aliases and package names.", + "format": "csv", + "mediatype": "plain/csv", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.csv", + "schema": { + "fields": [ + { + "name": "alias", + "title": "Alias", + "description": "Alias.", + "type": "string", + "format": "default" + }, + { + "name": "pkg", + "title": "Package Name", + "description": "Package name.", + "type": "string", + "format": "default" + } + ] + } + } + ], + "sources": [], + "keywords": [ + "stdlib", + "namespace", + "aliases", + "package", + "name", + "pkg" + ], + "license": "PDDL-1.0 AND CC0-1.0" +} From dfe4c8ef0235834c1e6471bede00c447926878db Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 21:28:02 -0700 Subject: [PATCH 057/142] Add data package files --- .../@stdlib/namespace/pkg2alias/LICENSE | 356 ++++++++++++++++++ .../@stdlib/namespace/pkg2alias/README.md | 14 + .../namespace/pkg2alias/datapackage.json | 56 +++ 3 files changed, 426 insertions(+) create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/LICENSE create mode 100644 lib/node_modules/@stdlib/namespace/pkg2alias/datapackage.json diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/LICENSE b/lib/node_modules/@stdlib/namespace/pkg2alias/LICENSE new file mode 100644 index 000000000000..dc6d53e33997 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/LICENSE @@ -0,0 +1,356 @@ +The use of the database is licensed under an Open Data Commons Public Domain +Dedication & License 1.0 (PDDL 1.0), while the database contents are licensed +under Creative Commons Zero v1.0 Universal (CC0 1.0). 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It replaces any earlier understandings, agreements or representations with respect to the Work not specified here. + +6.3 This Document does not affect any rights that You or anyone else may independently have under any applicable law to make any use of this Work, including (for jurisdictions where this Document is a licence) fair dealing, fair use, database exceptions, or any other legally recognised limitation or exception to infringement of copyright or other applicable laws. + +6.4 This Document takes effect in the relevant jurisdiction in which the Document terms are sought to be enforced. If the rights waived or granted under applicable law in the relevant jurisdiction includes additional rights not waived or granted under this Document, these additional rights are included in this Document in order to meet the intent of this Document. diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/README.md b/lib/node_modules/@stdlib/namespace/pkg2alias/README.md index 38e68815f974..f4762cf27c59 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/README.md +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/README.md @@ -170,10 +170,24 @@ base.sin + + +## License + +The data files (databases) are licensed under an [Open Data Commons Public Domain Dedication & License 1.0][pddl-1.0] and their contents are licensed under [Creative Commons Zero v1.0 Universal][cc0]. The software is licensed under [Apache License, Version 2.0][apache-license]. + + +
+[pddl-1.0]: http://opendatacommons.org/licenses/pddl/1.0/ + +[cc0]: https://creativecommons.org/publicdomain/zero/1.0 + +[apache-license]: https://www.apache.org/licenses/LICENSE-2.0 +
diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/datapackage.json b/lib/node_modules/@stdlib/namespace/pkg2alias/datapackage.json new file mode 100644 index 000000000000..24d5eedb045a --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/datapackage.json @@ -0,0 +1,56 @@ +{ + "name": "stdlib-pkg2alias", + "version": "", + "title": "Standard Library Package Names and Aliases", + "description": "A mapping between standard library package names and aliases.", + "resources": [ + { + "name": "stdlib-pkg2alias-json", + "title": "Standard Library Package Names and Aliases", + "description": "A mapping between standard library package names and aliases.", + "format": "json", + "mediatype": "application/json", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.json" + }, + { + "name": "stdlib-pkg2alias-csv", + "title": "Standard Library Package Names and Aliases", + "description": "A mapping between standard library package names and aliases.", + "format": "csv", + "mediatype": "plain/csv", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.csv", + "schema": { + "fields": [ + { + "name": "pkg", + "title": "Package Name", + "description": "Package name.", + "type": "string", + "format": "default" + }, + { + "name": "alias", + "title": "Alias", + "description": "Alias.", + "type": "string", + "format": "default" + } + ] + } + } + ], + "sources": [], + "keywords": [ + "stdlib", + "namespace", + "aliases", + "package", + "name", + "pkg" + ], + "license": "PDDL-1.0 AND CC0-1.0" +} From 5bd0e325985732f661612f3c69a3b3d01d51ffa4 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 21:30:22 -0700 Subject: [PATCH 058/142] Add data package files --- .../@stdlib/namespace/alias2related/LICENSE | 356 ++++++++++++++++++ .../@stdlib/namespace/alias2related/README.md | 14 + .../namespace/alias2related/datapackage.json | 56 +++ 3 files changed, 426 insertions(+) create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/LICENSE create mode 100644 lib/node_modules/@stdlib/namespace/alias2related/datapackage.json diff --git a/lib/node_modules/@stdlib/namespace/alias2related/LICENSE b/lib/node_modules/@stdlib/namespace/alias2related/LICENSE new file mode 100644 index 000000000000..dc6d53e33997 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/LICENSE @@ -0,0 +1,356 @@ +The use of the database is licensed under an Open Data Commons Public Domain +Dedication & License 1.0 (PDDL 1.0), while the database contents are licensed +under Creative Commons Zero v1.0 Universal (CC0 1.0). 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It replaces any earlier understandings, agreements or representations with respect to the Work not specified here. + +6.3 This Document does not affect any rights that You or anyone else may independently have under any applicable law to make any use of this Work, including (for jurisdictions where this Document is a licence) fair dealing, fair use, database exceptions, or any other legally recognised limitation or exception to infringement of copyright or other applicable laws. + +6.4 This Document takes effect in the relevant jurisdiction in which the Document terms are sought to be enforced. If the rights waived or granted under applicable law in the relevant jurisdiction includes additional rights not waived or granted under this Document, these additional rights are included in this Document in order to meet the intent of this Document. diff --git a/lib/node_modules/@stdlib/namespace/alias2related/README.md b/lib/node_modules/@stdlib/namespace/alias2related/README.md index 0e713fc8ceb4..0152e8fb0f6c 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/README.md +++ b/lib/node_modules/@stdlib/namespace/alias2related/README.md @@ -164,10 +164,24 @@ $ stdlib-alias2related 'base.sin' + + +## License + +The data files (databases) are licensed under an [Open Data Commons Public Domain Dedication & License 1.0][pddl-1.0] and their contents are licensed under [Creative Commons Zero v1.0 Universal][cc0]. The software is licensed under [Apache License, Version 2.0][apache-license]. + + +
+[pddl-1.0]: http://opendatacommons.org/licenses/pddl/1.0/ + +[cc0]: https://creativecommons.org/publicdomain/zero/1.0 + +[apache-license]: https://www.apache.org/licenses/LICENSE-2.0 +
diff --git a/lib/node_modules/@stdlib/namespace/alias2related/datapackage.json b/lib/node_modules/@stdlib/namespace/alias2related/datapackage.json new file mode 100644 index 000000000000..5d3ec7cd46ab --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/alias2related/datapackage.json @@ -0,0 +1,56 @@ +{ + "name": "stdlib-alias2related", + "version": "", + "title": "Standard Library Aliases and Related Aliases", + "description": "A mapping between standard library aliases and related aliases.", + "resources": [ + { + "name": "stdlib-alias2related-json", + "title": "Standard Library Aliases and Related Aliases", + "description": "A mapping between standard library aliases and related aliases.", + "format": "json", + "mediatype": "application/json", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.json" + }, + { + "name": "stdlib-alias2related-csv", + "title": "Standard Library Aliases and Related Aliases", + "description": "A mapping between standard library aliases and related aliases.", + "format": "csv", + "mediatype": "plain/csv", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.csv", + "schema": { + "fields": [ + { + "name": "alias", + "title": "Alias", + "description": "Alias.", + "type": "string", + "format": "default" + }, + { + "name": "related", + "title": "Related", + "description": "Comma-delimited aliases.", + "type": "string", + "format": "default" + } + ] + } + } + ], + "sources": [], + "keywords": [ + "stdlib", + "namespace", + "aliases", + "package", + "name", + "related" + ], + "license": "PDDL-1.0 AND CC0-1.0" +} From 9fe282b0c3a48277bde4b37620bf3fdcea5aab37 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 21:36:46 -0700 Subject: [PATCH 059/142] Fix function name --- .../@stdlib/namespace/alias2related/lib/main.js | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2related/lib/main.js b/lib/node_modules/@stdlib/namespace/alias2related/lib/main.js index 0e7197ef0d30..ba8f92aede58 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/lib/main.js +++ b/lib/node_modules/@stdlib/namespace/alias2related/lib/main.js @@ -32,13 +32,13 @@ var ALIAS_TO_RELATED = require( './../data/data.json' ); * * @param {string} alias - alias * @throws {TypeError} must provide a string -* @returns {(StringArray|null)} related aliases +* @returns {(Array|StringArray|null)} related aliases * * @example -* var v = alias2pkg( 'base.sin' ); +* var v = alias2related( 'base.sin' ); * // returns [...] */ -function alias2pkg( alias ) { +function alias2related( alias ) { if ( !isString( alias ) ) { throw new TypeError( 'invalid argument. Must provide a string. Value: `' + alias + '`.' ); } @@ -51,4 +51,4 @@ function alias2pkg( alias ) { // EXPORTS // -module.exports = alias2pkg; +module.exports = alias2related; From d2de7f8225e2abd0cf7d014db1587ef3291532ea Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 21:42:05 -0700 Subject: [PATCH 060/142] Fix error message --- .../@stdlib/namespace/alias2related/scripts/build.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js b/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js index c7137d808289..e85690e8e9fe 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js +++ b/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js @@ -67,7 +67,7 @@ function main() { if ( alias ) { tmp.push( alias ); } else { - console.error( 'WARNING: unable to resolve related alias `'+related[j]+'` for `'+ns[i]+'`.' ); + console.error( 'WARNING: unable to resolve related alias `'+related[j]+'` for `'+ns[i].alias+'`.' ); } } json[ ns[i].alias ] = tmp; From c1bbb8c914d0c9d42ea212f9ee4c6db613451379 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 21:51:39 -0700 Subject: [PATCH 061/142] Add utility to return related package names --- .../@stdlib/namespace/pkg2related/LICENSE | 356 ++++ .../@stdlib/namespace/pkg2related/README.md | 190 ++ .../pkg2related/benchmark/benchmark.js | 55 + .../@stdlib/namespace/pkg2related/bin/cli | 66 + .../namespace/pkg2related/data/data.csv | 1887 +++++++++++++++++ .../namespace/pkg2related/data/data.json | 1 + .../namespace/pkg2related/datapackage.json | 58 + .../namespace/pkg2related/docs/repl.txt | 22 + .../pkg2related/docs/types/index.d.ts | 36 + .../namespace/pkg2related/docs/types/test.ts | 44 + .../namespace/pkg2related/docs/usage.txt | 8 + .../namespace/pkg2related/etc/cli_opts.json | 15 + .../namespace/pkg2related/examples/index.js | 41 + .../namespace/pkg2related/lib/index.js | 40 + .../@stdlib/namespace/pkg2related/lib/main.js | 54 + .../namespace/pkg2related/package.json | 70 + .../namespace/pkg2related/scripts/build.js | 99 + .../namespace/pkg2related/test/test.cli.js | 184 ++ .../namespace/pkg2related/test/test.js | 95 + 19 files changed, 3321 insertions(+) create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/LICENSE create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/README.md create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/benchmark/benchmark.js create mode 100755 lib/node_modules/@stdlib/namespace/pkg2related/bin/cli create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/data/data.json create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/datapackage.json create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/docs/usage.txt create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/etc/cli_opts.json create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/examples/index.js create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/lib/index.js create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/lib/main.js create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/package.json create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/scripts/build.js create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/test/test.cli.js create mode 100644 lib/node_modules/@stdlib/namespace/pkg2related/test/test.js diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/LICENSE b/lib/node_modules/@stdlib/namespace/pkg2related/LICENSE new file mode 100644 index 000000000000..dc6d53e33997 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/LICENSE @@ -0,0 +1,356 @@ +The use of the database is licensed under an Open Data Commons Public Domain +Dedication & License 1.0 (PDDL 1.0), while the database contents are licensed +under Creative Commons Zero v1.0 Universal (CC0 1.0). 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It replaces any earlier understandings, agreements or representations with respect to the Work not specified here. + +6.3 This Document does not affect any rights that You or anyone else may independently have under any applicable law to make any use of this Work, including (for jurisdictions where this Document is a licence) fair dealing, fair use, database exceptions, or any other legally recognised limitation or exception to infringement of copyright or other applicable laws. + +6.4 This Document takes effect in the relevant jurisdiction in which the Document terms are sought to be enforced. If the rights waived or granted under applicable law in the relevant jurisdiction includes additional rights not waived or granted under this Document, these additional rights are included in this Document in order to meet the intent of this Document. diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/README.md b/lib/node_modules/@stdlib/namespace/pkg2related/README.md new file mode 100644 index 000000000000..78e1e00015d9 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/README.md @@ -0,0 +1,190 @@ + + +# pkg2related + +> Return package names related to a specified package name. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var pkg2related = require( '@stdlib/namespace/pkg2related' ); +``` + +#### pkg2related( pkg ) + +Returns package names related to a specified package name. + +```javascript +var out = pkg2related( '@stdlib/math/base/special/sin' ); +// returns [...] +``` + +If provided an unrecognized package name, the function returns `null`. + +```javascript +var out = pkg2related( 'unrecognized_pkg_beep_boop_bop_bip' ); +// returns null +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + + + +```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var pkg2related = require( '@stdlib/namespace/pkg2related' ); + +var list; +var len; +var idx; +var pkg; +var v; +var i; + +list = aliases(); +len = list.length; + +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len-1 ); + v = list[ idx ]; + pkg = alias2pkg( v ); + console.log( 'alias: %s. related: %s.', v, pkg2related( pkg ).join( ', ' ) ); +} +``` + +
+ + + + + +* * * + +
+ +## CLI + + + +
+ +### Usage + +```text +Usage: stdlib-pkg2related [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```bash +$ stdlib-pkg2related '@stdlib/math/base/special/sin' +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +## License + +The data files (databases) are licensed under an [Open Data Commons Public Domain Dedication & License 1.0][pddl-1.0] and their contents are licensed under [Creative Commons Zero v1.0 Universal][cc0]. The software is licensed under [Apache License, Version 2.0][apache-license]. + + + + + +
+ +[pddl-1.0]: http://opendatacommons.org/licenses/pddl/1.0/ + +[cc0]: https://creativecommons.org/publicdomain/zero/1.0 + +[apache-license]: https://www.apache.org/licenses/LICENSE-2.0 + +
+ + diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/benchmark/benchmark.js b/lib/node_modules/@stdlib/namespace/pkg2related/benchmark/benchmark.js new file mode 100644 index 000000000000..804e7f7e59ec --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/benchmark/benchmark.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isStringArray = require( '@stdlib/assert/is-string-array' ).primitives; +var pkg = require( './../package.json' ).name; +var pkg2related = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var v; + var i; + + values = [ + '@stdlib/math/base/special/abs', + '@stdlib/math/base/special/cos', + '@stdlib/math/base/special/sin' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = pkg2related( values[ i%values.length ] ); + if ( typeof v !== 'object' ) { + b.fail( 'should return an object' ); + } + } + b.toc(); + if ( v.length > 0 && !isStringArray( v ) ) { + b.fail( 'should return an array of strings' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/bin/cli b/lib/node_modules/@stdlib/namespace/pkg2related/bin/cli new file mode 100755 index 000000000000..2c915ed50ca3 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/bin/cli @@ -0,0 +1,66 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var readFileSync = require( '@stdlib/fs/read-file' ).sync; +var CLI = require( '@stdlib/tools/cli' ); +var pkg2related = require( './../lib' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var args; + var cli; + var out; + + // Create a command-line interface: + cli = new CLI({ + 'pkg': require( './../package.json' ), + 'options': require( './../etc/cli_opts.json' ), + 'help': readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }) + }); + + // Get any provided command-line arguments: + args = cli.args(); + + // Resolve related package names... + out = pkg2related( args[ 0 ] ); + if ( out ) { + if ( out.length ) { + console.log( out.join( '\n' ) ); // eslint-disable-line no-console + } + } else { + cli.exit( 1 ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv new file mode 100644 index 000000000000..3400d364a337 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv @@ -0,0 +1,1887 @@ +"@stdlib/datasets/afinn-96","@stdlib/datasets/afinn-111" +"@stdlib/datasets/afinn-111","@stdlib/datasets/afinn-96" +"@stdlib/namespace/alias2pkg","@stdlib/namespace/alias2related,@stdlib/namespace/aliases,@stdlib/namespace/pkg2alias" +"@stdlib/namespace/alias2related","@stdlib/namespace/alias2pkg,@stdlib/namespace/aliases" +"@stdlib/namespace/aliases","@stdlib/namespace/alias2pkg,@stdlib/namespace/alias2related,@stdlib/namespace/pkg2alias" +"@stdlib/buffer/alloc-unsafe","@stdlib/buffer/ctor,@stdlib/buffer/from-array,@stdlib/buffer/from-arraybuffer,@stdlib/buffer/from-buffer,@stdlib/buffer/from-string" +"@stdlib/stats/anova1","" +"@stdlib/datasets/anscombes-quartet","" +"@stdlib/utils/any","@stdlib/utils/any-by,@stdlib/utils/every,@stdlib/utils/for-each,@stdlib/utils/none,@stdlib/utils/some" +"@stdlib/utils/any-by","@stdlib/utils/async/any-by,@stdlib/utils/any-by-right,@stdlib/utils/every-by,@stdlib/utils/for-each,@stdlib/utils/none-by,@stdlib/utils/some-by" +"@stdlib/utils/async/any-by","@stdlib/utils/any-by,@stdlib/utils/async/any-by-right,@stdlib/utils/async/every-by,@stdlib/utils/async/for-each,@stdlib/utils/async/none-by,@stdlib/utils/async/some-by" +"@stdlib/utils/any-by-right","@stdlib/utils/any-by,@stdlib/utils/async/any-by-right,@stdlib/utils/every-by-right,@stdlib/utils/for-each-right,@stdlib/utils/none-by-right,@stdlib/utils/some-by-right" +"@stdlib/utils/async/any-by-right","@stdlib/utils/async/any-by,@stdlib/utils/any-by-right,@stdlib/utils/async/every-by-right,@stdlib/utils/async/for-each-right,@stdlib/utils/async/none-by-right,@stdlib/utils/async/some-by-right" +"@stdlib/constants/math/float64-apery","" +"@stdlib/utils/append","@stdlib/utils/prepend,@stdlib/utils/push" +"@stdlib/os/arch","@stdlib/os/platform" +"@stdlib/utils/argument-function","@stdlib/utils/constant-function,@stdlib/utils/identity-function" +"@stdlib/process/argv","@stdlib/process/env" +"@stdlib/ndarray/array","@stdlib/ndarray/ctor" +"@stdlib/buffer/from-array","@stdlib/buffer/ctor,@stdlib/buffer/from-arraybuffer,@stdlib/buffer/from-buffer,@stdlib/buffer/from-string" +"@stdlib/array/to-iterator","@stdlib/array/from-iterator,@stdlib/array/to-circular-iterator,@stdlib/array/to-iterator-right,@stdlib/array/to-strided-iterator" +"@stdlib/array/to-iterator-right","@stdlib/array/from-iterator,@stdlib/array/to-iterator" +"@stdlib/array/buffer","@stdlib/buffer/ctor,@stdlib/array/float32,@stdlib/array/float64,@stdlib/array/int16,@stdlib/array/int32,@stdlib/array/int8,@stdlib/array/shared-buffer,@stdlib/array/uint16,@stdlib/array/uint32,@stdlib/array/uint8,@stdlib/array/uint8c" +"@stdlib/buffer/from-arraybuffer","@stdlib/buffer/ctor,@stdlib/buffer/from-array,@stdlib/buffer/from-buffer,@stdlib/buffer/from-string" +"@stdlib/array/ctors","@stdlib/array/typed-ctors" +"@stdlib/array/dtype","@stdlib/array/dtypes" +"@stdlib/array/dtypes","@stdlib/array/typed-dtypes,@stdlib/ndarray/dtypes" +"@stdlib/array/min-dtype","@stdlib/array/dtypes,@stdlib/array/promotion-rules,@stdlib/array/safe-casts" +"@stdlib/array/next-dtype","@stdlib/array/dtype,@stdlib/array/dtypes" +"@stdlib/array/promotion-rules","@stdlib/array/dtypes,@stdlib/array/safe-casts,@stdlib/ndarray/promotion-rules" +"@stdlib/array/safe-casts","@stdlib/array/convert,@stdlib/array/convert-same,@stdlib/array/dtypes,@stdlib/array/same-kind-casts,@stdlib/ndarray/safe-casts" +"@stdlib/array/same-kind-casts","@stdlib/array/convert,@stdlib/array/convert-same,@stdlib/array/dtypes,@stdlib/array/safe-casts,@stdlib/ndarray/same-kind-casts" +"@stdlib/array/shape","@stdlib/ndarray/ctor" +"@stdlib/streams/node/from-array","@stdlib/streams/node/from-circular-array,@stdlib/streams/node/from-iterator,@stdlib/streams/node/from-strided-array" +"@stdlib/array/to-view-iterator","@stdlib/array/from-iterator,@stdlib/array/to-iterator,@stdlib/array/to-strided-iterator,@stdlib/array/to-view-iterator-right" +"@stdlib/array/to-view-iterator-right","@stdlib/array/from-iterator,@stdlib/array/to-iterator-right,@stdlib/array/to-strided-iterator,@stdlib/array/to-view-iterator" +"@stdlib/symbol/async-iterator","@stdlib/symbol/ctor,@stdlib/symbol/iterator" +"@stdlib/stats/bartlett-test","@stdlib/stats/vartest" +"@stdlib/math/base/special/abs","@stdlib/math/base/special/abs2" +"@stdlib/math/base/special/abs2","@stdlib/math/base/special/abs" +"@stdlib/math/base/utils/absolute-difference","@stdlib/math/base/utils/relative-difference,@stdlib/math/base/utils/float64-epsilon-difference" +"@stdlib/math/base/special/int32-abs","@stdlib/math/base/special/abs" +"@stdlib/math/base/special/acos","@stdlib/math/base/special/acosh,@stdlib/math/base/special/asin,@stdlib/math/base/special/atan" +"@stdlib/math/base/special/acosh","@stdlib/math/base/special/acos,@stdlib/math/base/special/asinh,@stdlib/math/base/special/atanh" +"@stdlib/math/base/special/acoth","@stdlib/math/base/special/acosh,@stdlib/math/base/special/asinh,@stdlib/math/base/special/atanh" +"@stdlib/math/base/special/acovercos","@stdlib/math/base/special/acoversin,@stdlib/math/base/special/avercos,@stdlib/math/base/special/covercos,@stdlib/math/base/special/vercos" +"@stdlib/math/base/special/acoversin","@stdlib/math/base/special/acovercos,@stdlib/math/base/special/aversin,@stdlib/math/base/special/coversin,@stdlib/math/base/special/versin" +"@stdlib/math/base/special/ahavercos","@stdlib/math/base/special/ahaversin,@stdlib/math/base/special/havercos,@stdlib/math/base/special/vercos" +"@stdlib/math/base/special/ahaversin","@stdlib/math/base/special/ahavercos,@stdlib/math/base/special/haversin,@stdlib/math/base/special/versin" +"@stdlib/math/base/special/asin","@stdlib/math/base/special/acos,@stdlib/math/base/special/asinh,@stdlib/math/base/special/atan" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/datapackage.json b/lib/node_modules/@stdlib/namespace/pkg2related/datapackage.json new file mode 100644 index 000000000000..b70a4ed791a8 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/datapackage.json @@ -0,0 +1,58 @@ +{ + "name": "stdlib-pkg2related", + "version": "", + "title": "Standard Library Package Names and Related Packages", + "description": "A mapping between standard library package names and related packages.", + "resources": [ + { + "name": "stdlib-pkg2related-json", + "title": "Standard Library Package Names and Related Packages", + "description": "A mapping between standard library package names and related packages.", + "format": "json", + "mediatype": "application/json", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.json" + }, + { + "name": "stdlib-pkg2related-csv", + "title": "Standard Library Package Names and Related Packages", + "description": "A mapping between standard library package names and related packages.", + "format": "csv", + "mediatype": "plain/csv", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.csv", + "schema": { + "fields": [ + { + "name": "pkg", + "title": "Package Name", + "description": "Package name.", + "type": "string", + "format": "default" + }, + { + "name": "related", + "title": "Related", + "description": "Comma-delimited package names.", + "type": "string", + "format": "default" + } + ] + } + } + ], + "sources": [], + "keywords": [ + "stdlib", + "namespace", + "package", + "packages", + "pkg", + "pkgs", + "name", + "related" + ], + "license": "PDDL-1.0 AND CC0-1.0" +} diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/docs/repl.txt b/lib/node_modules/@stdlib/namespace/pkg2related/docs/repl.txt new file mode 100644 index 000000000000..e8b0682f6ad0 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/docs/repl.txt @@ -0,0 +1,22 @@ + +{{alias}}( pkg ) + Returns package names related to a specified package name. + + Parameters + ---------- + pkg: string + Package name. + + Returns + ------- + out: Array|null + Related package names. + + Examples + -------- + > var v = {{alias}}( '@stdlib/math/base/special/sin' ) + [...] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/docs/types/index.d.ts b/lib/node_modules/@stdlib/namespace/pkg2related/docs/types/index.d.ts new file mode 100644 index 000000000000..43d339f32923 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/docs/types/index.d.ts @@ -0,0 +1,36 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Returns package names related to a specified package name. +* +* @param pkg - package name +* @returns related package names +* +* @example +* var out = pkg2related( '@stdlib/math/base/special/sin' ); +* // returns [...] +*/ +declare function pkg2related( pkg: string ): Array | null; + + +// EXPORTS // + +export = pkg2related; diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/docs/types/test.ts b/lib/node_modules/@stdlib/namespace/pkg2related/docs/types/test.ts new file mode 100644 index 000000000000..c35a499a0e63 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import pkg2related = require( './index' ); + + +// TESTS // + +// The function returns an array of strings or null... +{ + pkg2related( 'base.sin' ); // $ExpectType string[] | null +} + +// The compiler throws an error if the function is not provided a string... +{ + pkg2related( 5 ); // $ExpectError + pkg2related( true ); // $ExpectError + pkg2related( false ); // $ExpectError + pkg2related( null ); // $ExpectError + pkg2related( undefined ); // $ExpectError + pkg2related( [] ); // $ExpectError + pkg2related( {} ); // $ExpectError + pkg2related( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + pkg2related( 'base.sin', 'beep' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/docs/usage.txt b/lib/node_modules/@stdlib/namespace/pkg2related/docs/usage.txt new file mode 100644 index 000000000000..ad9f9c201ee7 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/docs/usage.txt @@ -0,0 +1,8 @@ + +Usage: stdlib-pkg2related [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. + diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/etc/cli_opts.json b/lib/node_modules/@stdlib/namespace/pkg2related/etc/cli_opts.json new file mode 100644 index 000000000000..92119c456962 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/etc/cli_opts.json @@ -0,0 +1,15 @@ +{ + "string": [], + "boolean": [ + "help", + "version" + ], + "alias": { + "help": [ + "h" + ], + "version": [ + "V" + ] + } +} diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/examples/index.js b/lib/node_modules/@stdlib/namespace/pkg2related/examples/index.js new file mode 100644 index 000000000000..370ed08d836e --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var pkg2related = require( './../lib' ); + +var list; +var len; +var idx; +var pkg; +var v; +var i; + +list = aliases(); +len = list.length; + +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len-1 ); + v = list[ idx ]; + pkg = alias2pkg( v ); + console.log( 'alias: %s. related: %s.', v, pkg2related( pkg ).join( ', ' ) ); +} diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/lib/index.js b/lib/node_modules/@stdlib/namespace/pkg2related/lib/index.js new file mode 100644 index 000000000000..6cffe00b0fbb --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return package names related to a specified package name. +* +* @module @stdlib/namespace/pkg2related +* +* @example +* var pkg2related = require( '@stdlib/namespace/pkg2related' ); +* +* var v = pkg2related( '@stdlib/math/base/special/sin' ); +* // returns [...] +*/ + +// MODULES // + +var pkg2related = require( './main.js' ); + + +// EXPORTS // + +module.exports = pkg2related; diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/lib/main.js b/lib/node_modules/@stdlib/namespace/pkg2related/lib/main.js new file mode 100644 index 000000000000..b5b18e220ec4 --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/lib/main.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var PKG_TO_RELATED = require( './../data/data.json' ); + + +// MAIN // + +/** +* Returns package names related to a specified package name. +* +* @param {string} pkg - package name +* @throws {TypeError} must provide a string +* @returns {(Array|StringArray|null)} related package names +* +* @example +* var v = pkg2related( '@stdlib/math/base/special/sin' ); +* // returns [...] +*/ +function pkg2related( pkg ) { + if ( !isString( pkg ) ) { + throw new TypeError( 'invalid argument. Must provide a string. Value: `' + pkg + '`.' ); + } + if ( hasOwnProp( PKG_TO_RELATED, pkg ) ) { + return PKG_TO_RELATED[ pkg ].slice(); + } + return null; +} + + +// EXPORTS // + +module.exports = pkg2related; diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/package.json b/lib/node_modules/@stdlib/namespace/pkg2related/package.json new file mode 100644 index 000000000000..6106eab4162c --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/namespace/pkg2related", + "version": "0.0.0", + "description": "Return package names related to a specified package name.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "bin": { + "stdlib-pkg2related": "./bin/cli" + }, + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "bin": "./bin", + "data": "./data", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "standard", + "library", + "lib", + "namespace", + "packages", + "package", + "name", + "pkg", + "pkgs", + "related", + "see", + "also" + ] +} diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/scripts/build.js b/lib/node_modules/@stdlib/namespace/pkg2related/scripts/build.js new file mode 100644 index 000000000000..b22c619f4aff --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/scripts/build.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var logger = require( 'debug' ); +var writeFile = require( '@stdlib/fs/write-file' ).sync; +var namespace = require( '@stdlib/namespace' ); +var pkg2alias = require( '@stdlib/namespace/pkg2alias' ); +var objectKeys = require( '@stdlib/utils/keys' ); + + +// VARIABLES // + +var debug = logger( 'namespace:pkg2related:build' ); + +// Output file paths: +var OUTPUT_JSON = resolve( __dirname, '..', 'data', 'data.json' ); +var OUTPUT_CSV = resolve( __dirname, '..', 'data', 'data.csv' ); + + +// FUNCTIONS // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var related; + var alias; + var fopts; + var keys; + var json; + var tmp; + var csv; + var ns; + var i; + var j; + + debug( 'Extracting namespace package data...' ); + ns = namespace(); + json = {}; + for ( i = 0; i < ns.length; i++ ) { + related = ns[ i ].related.slice(); + + // Check that each related package actually corresponds to an alias in the namespace, as sometimes packages are added to the `related` field before they are actually created... + tmp = []; + for ( j = 0; j < related.length; j++ ) { + alias = pkg2alias( related[ j ] ); + if ( alias ) { + tmp.push( related[ j ] ); + } else { + console.error( 'WARNING: unable to resolve related package `'+related[j]+'` for `'+ns[i].alias+'`.' ); + } + } + json[ ns[i].path ] = tmp; + } + + debug( 'Writing to JSON file...' ); + fopts = { + 'encoding': 'utf8' + }; + writeFile( OUTPUT_JSON, JSON.stringify( json ), fopts ); + + debug( 'Writing to CSV file...' ); + fopts = { + 'encoding': 'utf8' + }; + keys = objectKeys( json ); + csv = ''; + for ( i = 0; i < keys.length; i++ ) { + csv += '"' + keys[ i ] + '","' + json[ keys[i] ].join( ',' ) + '"\n'; // Note: ensures trailing newline + } + writeFile( OUTPUT_CSV, csv, fopts ); +} + + +// MAIN // + +main(); diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/test/test.cli.js b/lib/node_modules/@stdlib/namespace/pkg2related/test/test.cli.js new file mode 100644 index 000000000000..ef02c11f51ac --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/test/test.cli.js @@ -0,0 +1,184 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var exec = require( 'child_process' ).exec; +var tape = require( 'tape' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); +var readFileSync = require( '@stdlib/fs/read-file' ).sync; + + +// VARIABLES // + +var fpath = resolve( __dirname, '..', 'bin', 'cli' ); +var opts = { + 'skip': IS_BROWSER || IS_WINDOWS +}; + + +// FIXTURES // + +var PKG_VERSION = require( './../package.json' ).version; + + +// TESTS // + +tape( 'command-line interface', function test( t ) { + t.ok( true, __filename ); + t.end(); +}); + +tape( 'when invoked with a `--help` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '--help' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-h` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '-h' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `--version` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '--version' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-V` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '-V' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'the command-line interface prints related package names', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '@stdlib/math/base/special/sin' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + stdout = stdout.toString().split( '\n' ); + + // Greater than 1 in order to include the trailing newline: + t.strictEqual( stdout.length > 1, true, 'prints related packages' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + } + t.end(); + } +}); + +tape( 'if unable to resolve a package name, the command-line interface sets a non-zero exit code', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + 'fjaldfjadljfeoejreandfljasdfjadsfjs' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.pass( error.message ); + t.strictEqual( error.code, 1, 'expected exit code' ); + } + t.strictEqual( stdout.toString(), '', 'does not print to` stdout`' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + t.end(); + } +}); diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/test/test.js b/lib/node_modules/@stdlib/namespace/pkg2related/test/test.js new file mode 100644 index 000000000000..c4984679a92c --- /dev/null +++ b/lib/node_modules/@stdlib/namespace/pkg2related/test/test.js @@ -0,0 +1,95 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var DATA = require( './../data/data.json' ); +var pkg2related = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof pkg2related, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a string', function test( t ) { + var values; + var i; + + values = [ + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + pkg2related( value ); + }; + } +}); + +tape( 'the function returns related package names', function test( t ) { + var expected; + var actual; + var list; + var pkg; + var i; + + list = aliases(); + for ( i = 0; i < list.length; i++ ) { + pkg = alias2pkg( list[i] ); + expected = DATA[ pkg ]; + actual = pkg2related( pkg ); + t.deepEqual( actual, expected, 'returns expected value for '+list[i] ); + } + t.end(); +}); + +tape( 'the function returns `null` if provided an unrecognized package name', function test( t ) { + var values; + var i; + + values = [ + 'adfkaljdfdsafs', + 'adklfadjflajdslfjalsdf', + 'adflkajdlkfjasdlkfjsadlkfjlasdjflsdjfla' + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( pkg2related( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); From 34be4029c03b4848e843014f31401bc43e214341 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 21:53:11 -0700 Subject: [PATCH 062/142] Disable lint rule --- .../@stdlib/namespace/alias2related/scripts/build.js | 2 +- lib/node_modules/@stdlib/namespace/pkg2related/scripts/build.js | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js b/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js index e85690e8e9fe..93b8850273a8 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js +++ b/lib/node_modules/@stdlib/namespace/alias2related/scripts/build.js @@ -67,7 +67,7 @@ function main() { if ( alias ) { tmp.push( alias ); } else { - console.error( 'WARNING: unable to resolve related alias `'+related[j]+'` for `'+ns[i].alias+'`.' ); + console.error( 'WARNING: unable to resolve related alias `'+related[j]+'` for `'+ns[i].alias+'`.' ); // eslint-disable-line no-console } } json[ ns[i].alias ] = tmp; diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/scripts/build.js b/lib/node_modules/@stdlib/namespace/pkg2related/scripts/build.js index b22c619f4aff..168ce3b1055c 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/scripts/build.js +++ b/lib/node_modules/@stdlib/namespace/pkg2related/scripts/build.js @@ -69,7 +69,7 @@ function main() { if ( alias ) { tmp.push( related[ j ] ); } else { - console.error( 'WARNING: unable to resolve related package `'+related[j]+'` for `'+ns[i].alias+'`.' ); + console.error( 'WARNING: unable to resolve related package `'+related[j]+'` for `'+ns[i].alias+'`.' ); // eslint-disable-line no-console } } json[ ns[i].path ] = tmp; From ecaea40ec2ecfc09038cf8e6df70e81f7d89691b Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 21:53:42 -0700 Subject: [PATCH 063/142] Add task to generate mapping between related packages --- tools/make/lib/docs/repl.mk | 12 +++++++++++- 1 file changed, 11 insertions(+), 1 deletion(-) diff --git a/tools/make/lib/docs/repl.mk b/tools/make/lib/docs/repl.mk index 9a1b57da84cc..7ef2eee30637 100644 --- a/tools/make/lib/docs/repl.mk +++ b/tools/make/lib/docs/repl.mk @@ -22,7 +22,7 @@ # # This target generates REPL documentation. -repl-docs: repl-help repl-examples repl-aliases repl-alias2pkg repl-pkg2alias repl-alias2related +repl-docs: repl-help repl-examples repl-aliases repl-alias2pkg repl-pkg2alias repl-alias2related repl-pkg2related .PHONY: repl-docs @@ -85,3 +85,13 @@ repl-alias2related: $(NODE_MODULES) $(SRC_DIR)/@stdlib/namespace/alias2related/s $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/namespace/alias2related/scripts/build.js" .PHONY: repl-alias2related + + +# Build the mapping between REPL package names and related packages. +# +# This target rebuilds the REPL database. + +repl-pkg2related: $(NODE_MODULES) $(SRC_DIR)/@stdlib/namespace/pkg2related/scripts/build.js + $(QUIET) $(NODE) "$(SRC_DIR)/@stdlib/namespace/pkg2related/scripts/build.js" + +.PHONY: repl-pkg2related From b4af5f480849624fd28872e2ed3a15428facf746 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 15 Mar 2019 21:55:51 -0700 Subject: [PATCH 064/142] Update namespace --- .../@stdlib/namespace/alias2pkg/data/data.csv | 1 + .../@stdlib/namespace/alias2pkg/data/data.json | 2 +- .../@stdlib/namespace/alias2related/data/data.csv | 5 +++-- .../@stdlib/namespace/alias2related/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.txt | 1 + .../@stdlib/namespace/lib/namespace/p.js | 12 ++++++++++++ .../@stdlib/namespace/pkg2alias/data/data.csv | 1 + .../@stdlib/namespace/pkg2alias/data/data.json | 2 +- .../@stdlib/namespace/pkg2related/data/data.csv | 5 +++-- .../@stdlib/namespace/pkg2related/data/data.json | 2 +- lib/node_modules/@stdlib/repl/code-blocks/lib/db.js | 1 + lib/node_modules/@stdlib/repl/help/lib/db.js | 5 +++-- 13 files changed, 30 insertions(+), 11 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index e261d2204d47..40a0b037cf33 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1584,6 +1584,7 @@ pick,"@stdlib/utils/pick" pickBy,"@stdlib/utils/pick-by" PINF,"@stdlib/constants/math/float64-pinf" pkg2alias,"@stdlib/namespace/pkg2alias" +pkg2related,"@stdlib/namespace/pkg2related" PLATFORM,"@stdlib/os/platform" plot,"@stdlib/plot" Plot,"@stdlib/plot/ctor" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index 988423840e28..3b20f3bdcf60 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ -{"AFINN_96":"@stdlib/datasets/afinn-96","AFINN_111":"@stdlib/datasets/afinn-111","alias2pkg":"@stdlib/namespace/alias2pkg","alias2related":"@stdlib/namespace/alias2related","aliases":"@stdlib/namespace/aliases","allocUnsafe":"@stdlib/buffer/alloc-unsafe","anova1":"@stdlib/stats/anova1","ANSCOMBES_QUARTET":"@stdlib/datasets/anscombes-quartet","any":"@stdlib/utils/any","anyBy":"@stdlib/utils/any-by","anyByAsync":"@stdlib/utils/async/any-by","anyByRight":"@stdlib/utils/any-by-right","anyByRightAsync":"@stdlib/utils/async/any-by-right","APERY":"@stdlib/constants/math/float64-apery","append":"@stdlib/utils/append","ARCH":"@stdlib/os/arch","argumentFunction":"@stdlib/utils/argument-function","ARGV":"@stdlib/process/argv","array":"@stdlib/ndarray/array","array2buffer":"@stdlib/buffer/from-array","array2iterator":"@stdlib/array/to-iterator","array2iteratorRight":"@stdlib/array/to-iterator-right","ArrayBuffer":"@stdlib/array/buffer","arraybuffer2buffer":"@stdlib/buffer/from-arraybuffer","arrayCtors":"@stdlib/array/ctors","arrayDataType":"@stdlib/array/dtype","arrayDataTypes":"@stdlib/array/dtypes","arrayMinDataType":"@stdlib/array/min-dtype","arrayNextDataType":"@stdlib/array/next-dtype","arrayPromotionRules":"@stdlib/array/promotion-rules","arraySafeCasts":"@stdlib/array/safe-casts","arraySameKindCasts":"@stdlib/array/same-kind-casts","arrayShape":"@stdlib/array/shape","arrayStream":"@stdlib/streams/node/from-array","arrayview2iterator":"@stdlib/array/to-view-iterator","arrayview2iteratorRight":"@stdlib/array/to-view-iterator-right","AsyncIteratorSymbol":"@stdlib/symbol/async-iterator","bartlettTest":"@stdlib/stats/bartlett-test","base.abs":"@stdlib/math/base/special/abs","base.abs2":"@stdlib/math/base/special/abs2","base.absdiff":"@stdlib/math/base/utils/absolute-difference","base.absInt32":"@stdlib/math/base/special/int32-abs","base.acos":"@stdlib/math/base/special/acos","base.acosh":"@stdlib/math/base/special/acosh","base.acoth":"@stdlib/math/base/special/acoth","base.acovercos":"@stdlib/math/base/special/acovercos","base.acoversin":"@stdlib/math/base/special/acoversin","base.ahavercos":"@stdlib/math/base/special/ahavercos","base.ahaversin":"@stdlib/math/base/special/ahaversin","base.asin":"@stdlib/math/base/special/asin","base.asinh":"@stdlib/math/base/special/asinh","base.atan":"@stdlib/math/base/special/atan","base.atan2":"@stdlib/math/base/special/atan2","base.atanh":"@stdlib/math/base/special/atanh","base.avercos":"@stdlib/math/base/special/avercos","base.aversin":"@stdlib/math/base/special/aversin","base.bernoulli":"@stdlib/math/base/special/bernoulli","base.besselj0":"@stdlib/math/base/special/besselj0","base.besselj1":"@stdlib/math/base/special/besselj1","base.bessely0":"@stdlib/math/base/special/bessely0","base.bessely1":"@stdlib/math/base/special/bessely1","base.beta":"@stdlib/math/base/special/beta","base.betainc":"@stdlib/math/base/special/betainc","base.betaincinv":"@stdlib/math/base/special/betaincinv","base.betaln":"@stdlib/math/base/special/betaln","base.binet":"@stdlib/math/base/special/binet","base.binomcoef":"@stdlib/math/base/special/binomcoef","base.binomcoefln":"@stdlib/math/base/special/binomcoefln","base.boxcox":"@stdlib/math/base/special/boxcox","base.boxcox1p":"@stdlib/math/base/special/boxcox1p","base.boxcox1pinv":"@stdlib/math/base/special/boxcox1pinv","base.boxcoxinv":"@stdlib/math/base/special/boxcoxinv","base.cabs":"@stdlib/math/base/complex/abs","base.cabs2":"@stdlib/math/base/complex/abs2","base.cadd":"@stdlib/math/base/complex/add","base.cbrt":"@stdlib/math/base/special/cbrt","base.cceil":"@stdlib/math/base/complex/ceil","base.cceiln":"@stdlib/math/base/complex/ceiln","base.ccis":"@stdlib/math/base/complex/cis","base.cdiv":"@stdlib/math/base/complex/divide","base.ceil":"@stdlib/math/base/special/ceil","base.ceil2":"@stdlib/math/base/special/ceil2","base.ceil10":"@stdlib/math/base/special/ceil10","base.ceilb":"@stdlib/math/base/special/ceilb","base.ceiln":"@stdlib/math/base/special/ceiln","base.ceilsd":"@stdlib/math/base/special/ceilsd","base.cexp":"@stdlib/math/base/complex/exp","base.cflipsign":"@stdlib/math/base/complex/flipsign","base.cfloor":"@stdlib/math/base/complex/floor","base.cfloorn":"@stdlib/math/base/complex/floorn","base.cinv":"@stdlib/math/base/complex/inv","base.clamp":"@stdlib/math/base/special/clamp","base.cmul":"@stdlib/math/base/complex/multiply","base.cneg":"@stdlib/math/base/complex/negate","base.continuedFraction":"@stdlib/math/base/tools/continued-fraction","base.copysign":"@stdlib/math/base/special/copysign","base.cos":"@stdlib/math/base/special/cos","base.cosh":"@stdlib/math/base/special/cosh","base.cosm1":"@stdlib/math/base/special/cosm1","base.cospi":"@stdlib/math/base/special/cospi","base.covercos":"@stdlib/math/base/special/covercos","base.coversin":"@stdlib/math/base/special/coversin","base.cphase":"@stdlib/math/base/complex/phase","base.cpolar":"@stdlib/math/base/complex/polar","base.cround":"@stdlib/math/base/complex/round","base.croundn":"@stdli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araswamy/variance","base.dists.laplace.cdf":"@stdlib/stats/base/dists/laplace/cdf","base.dists.laplace.entropy":"@stdlib/stats/base/dists/laplace/entropy","base.dists.laplace.kurtosis":"@stdlib/stats/base/dists/laplace/kurtosis","base.dists.laplace.Laplace":"@stdlib/stats/base/dists/laplace/ctor","base.dists.laplace.logcdf":"@stdlib/stats/base/dists/laplace/logcdf","base.dists.laplace.logpdf":"@stdlib/stats/base/dists/laplace/logpdf","base.dists.laplace.mean":"@stdlib/stats/base/dists/laplace/mean","base.dists.laplace.median":"@stdlib/stats/base/dists/laplace/median","base.dists.laplace.mgf":"@stdlib/stats/base/dists/laplace/mgf","base.dists.laplace.mode":"@stdlib/stats/base/dists/laplace/mode","base.dists.laplace.pdf":"@stdlib/stats/base/dists/laplace/pdf","base.dists.laplace.quantile":"@stdlib/stats/base/dists/laplace/quantile","base.dists.laplace.skewness":"@stdlib/stats/base/dists/laplace/skewness","base.dists.laplace.stdev":"@stdlib/stats/base/dists/laplace/stdev","base.dists.laplace.variance":"@stdlib/stats/base/dists/laplace/variance","base.dists.levy.cdf":"@stdlib/stats/base/dists/levy/cdf","base.dists.levy.entropy":"@stdlib/stats/base/dists/levy/entropy","base.dists.levy.Levy":"@stdlib/stats/base/dists/levy/ctor","base.dists.levy.logcdf":"@stdlib/stats/base/dists/levy/logcdf","base.dists.levy.logpdf":"@stdlib/stats/base/dists/levy/logpdf","base.dists.levy.mean":"@stdlib/stats/base/dists/levy/mean","base.dists.levy.median":"@stdlib/stats/base/dists/levy/median","base.dists.levy.mode":"@stdlib/stats/base/dists/levy/mode","base.dists.levy.pdf":"@stdlib/stats/base/dists/levy/pdf","base.dists.levy.quantile":"@stdlib/stats/base/dists/levy/quantile","base.dists.levy.stdev":"@stdlib/stats/base/dists/levy/stdev","base.dists.levy.variance":"@stdlib/stats/base/dists/levy/variance","base.dists.logistic.cdf":"@stdlib/stats/base/dists/logistic/cdf","base.dists.logistic.entropy":"@stdlib/stats/base/dists/logistic/entropy","base.dists.logistic.kurtosis":"@stdlib/stats/base/dists/logistic/kurtosis","base.dists.logistic.logcdf":"@stdlib/stats/base/dists/logistic/logcdf","base.dists.logistic.Logistic":"@stdlib/stats/base/dists/logistic/ctor","base.dists.logistic.logpdf":"@stdlib/stats/base/dists/logistic/logpdf","base.dists.logistic.mean":"@stdlib/stats/base/dists/logistic/mean","base.dists.logistic.median":"@stdlib/stats/base/dists/logistic/median","base.dists.logistic.mgf":"@stdlib/stats/base/dists/logistic/mgf","base.dists.logistic.mode":"@stdlib/stats/base/dists/logistic/mode","base.dists.logistic.pdf":"@stdlib/stats/base/dists/logistic/pdf","base.dists.logistic.quantile":"@stdlib/stats/base/dists/logistic/quantile","base.dists.logistic.skewness":"@stdlib/stats/base/dists/logistic/skewness","base.dists.logistic.stdev":"@stdlib/stats/base/dists/logistic/stdev","base.dists.logistic.variance":"@stdlib/stats/base/dists/logistic/variance","base.dists.lognormal.cdf":"@stdlib/stats/base/dists/lognormal/cdf","base.dists.lognormal.entropy":"@stdlib/stats/base/dists/lognormal/entropy","base.dists.lognormal.kurtosis":"@stdlib/stats/base/dists/lognormal/kurtosis","base.dists.lognormal.LogNormal":"@stdlib/stats/base/dists/lognormal/ctor","base.dists.lognormal.logpdf":"@stdlib/stats/base/dists/lognormal/logpdf","base.dists.lognormal.mean":"@stdlib/stats/base/dists/lognormal/mean","base.dists.lognormal.median":"@stdlib/stats/base/dists/lognormal/median","base.dists.lognormal.mode":"@stdlib/stats/base/dists/lognormal/mode","base.dists.lognormal.pdf":"@stdlib/stats/base/dists/lognormal/pdf","base.dists.lognormal.quantile":"@stdlib/stats/base/dists/lognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdli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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv index 3b6a1dea672f..1245afd008de 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv @@ -1,7 +1,7 @@ AFINN_96,"AFINN_111" AFINN_111,"AFINN_96" alias2pkg,"alias2related,aliases,pkg2alias" -alias2related,"alias2pkg,aliases" +alias2related,"alias2pkg,aliases,pkg2related" aliases,"alias2pkg,alias2related,pkg2alias" allocUnsafe,"Buffer,array2buffer,arraybuffer2buffer,copyBuffer,string2buffer" anova1,"" @@ -1583,7 +1583,8 @@ PI_SQUARED,"PI" pick,"pickBy" pickBy,"pick" PINF,"NINF" -pkg2alias,"alias2pkg,aliases" +pkg2alias,"alias2pkg,aliases,pkg2related" +pkg2related,"alias2related,aliases,pkg2alias" PLATFORM,"ARCH" plot,"Plot" Plot,"plot" diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.json 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index 353c05d496a2..db66ada82290 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1584,6 +1584,7 @@ pick pickBy PINF pkg2alias +pkg2related PLATFORM plot Plot diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/p.js b/lib/node_modules/@stdlib/namespace/lib/namespace/p.js index 90ad728c6832..55903f5c2d85 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/p.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/p.js @@ -236,6 +236,18 @@ ns.push({ ] }); +ns.push({ + 'alias': 'pkg2related', + 'path': '@stdlib/namespace/pkg2related', + 'value': require( '@stdlib/namespace/pkg2related' ), + 'type': 'Function', + 'related': [ + '@stdlib/namespace/alias2related', + '@stdlib/namespace/aliases', + '@stdlib/namespace/pkg2alias' + ] +}); + ns.push({ 'alias': 'PLATFORM', 'path': '@stdlib/os/platform', diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index b69ec4dbb0a7..17eaa8f4b428 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -1584,6 +1584,7 @@ "@stdlib/utils/pick-by",pickBy "@stdlib/constants/math/float64-pinf",PINF "@stdlib/namespace/pkg2alias",pkg2alias +"@stdlib/namespace/pkg2related",pkg2related "@stdlib/os/platform",PLATFORM "@stdlib/plot",plot "@stdlib/plot/ctor",Plot diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index 59249b926353..9bdbab1e9e66 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ -{"@stdlib/datasets/afinn-96":"AFINN_96","@stdlib/datasets/afinn-111":"AFINN_111","@stdlib/namespace/alias2pkg":"alias2pkg","@stdlib/namespace/alias2related":"alias2related","@stdlib/namespace/aliases":"aliases","@stdlib/buffer/alloc-unsafe":"allocUnsafe","@stdlib/stats/anova1":"anova1","@stdlib/datasets/anscombes-quartet":"ANSCOMBES_QUARTET","@stdlib/utils/any":"any","@stdlib/utils/any-by":"anyBy","@stdlib/utils/async/any-by":"anyByAsync","@stdlib/utils/any-by-right":"anyByRight","@stdlib/utils/async/any-by-right":"anyByRightAsync","@stdlib/constants/math/float64-apery":"APERY","@stdlib/utils/append":"append","@stdlib/os/arch":"ARCH","@stdlib/utils/argument-function":"argumentFunction","@stdlib/process/argv":"ARGV","@stdlib/ndarray/array":"array","@stdlib/buffer/from-array":"array2buffer","@stdlib/array/to-iterator":"array2iterator","@stdlib/array/to-iterator-right":"array2iteratorRight","@stdlib/array/buffer":"ArrayBuffer","@stdlib/buffer/from-arraybuffer":"arraybuffer2buffer","@stdlib/array/ctors":"arrayCtors","@stdlib/array/dtype":"arrayDataType","@stdlib/array/dtypes":"arrayDataTypes","@stdlib/array/min-dtype":"arrayMinDataType","@stdlib/array/next-dtype":"arrayNextDataType","@stdlib/array/promotion-rules":"arrayPromotionRules","@stdlib/array/safe-casts":"arraySafeCasts","@stdlib/array/same-kind-casts":"arraySameKindCasts","@stdlib/array/shape":"arrayShape","@stdlib/streams/node/from-array":"arrayStream","@stdlib/array/to-view-iterator":"arrayview2iterator","@stdlib/array/to-view-iterator-right":"arrayview2iteratorRight","@stdlib/symbol/async-iterator":"AsyncIteratorSymbol","@stdlib/stats/bartlett-test":"bartlettTest","@stdlib/math/base/special/abs":"base.abs","@stdlib/math/base/special/abs2":"base.abs2","@stdlib/math/base/utils/absolute-difference":"base.absdiff","@stdlib/math/base/special/int32-abs":"base.absInt32","@stdlib/math/base/special/acos":"base.acos","@stdlib/math/base/special/acosh":"base.acosh","@stdlib/math/base/special/acoth":"base.acoth","@stdlib/math/base/special/acovercos":"base.acovercos","@stdlib/math/base/special/acoversin":"base.acoversin","@stdlib/math/base/special/ahavercos":"base.ahavercos","@stdlib/math/base/special/ahaversin":"base.ahaversin","@stdlib/math/base/special/asin":"base.asin","@stdlib/math/base/special/asinh":"base.asinh","@stdlib/math/base/special/atan":"base.atan","@stdlib/math/base/special/atan2":"base.atan2","@stdlib/math/base/special/atanh":"base.atanh","@stdlib/math/base/special/avercos":"base.avercos","@stdlib/math/base/special/aversin":"base.aversin","@stdlib/math/base/special/bernoulli":"base.bernoulli","@stdlib/math/base/special/besselj0":"base.besselj0","@stdlib/math/base/special/besselj1":"base.besselj1","@stdlib/math/base/special/bessely0":"base.bessely0","@stdlib/math/base/special/bessely1":"base.bessely1","@stdlib/math/base/special/beta":"base.beta","@stdlib/math/base/special/betainc":"base.betainc","@stdlib/math/base/special/betaincinv":"base.betaincinv","@stdlib/math/base/special/betaln":"base.betaln","@stdlib/math/base/special/binet":"base.binet","@stdlib/math/base/special/binomcoef":"base.binomcoef","@stdlib/math/base/special/binomcoefln":"base.binomcoefln","@stdlib/math/base/special/boxcox":"base.boxcox","@stdlib/math/base/special/boxcox1p":"base.boxcox1p","@stdlib/math/base/special/boxcox1pinv":"base.boxcox1pinv","@stdlib/math/base/special/boxcoxinv":"base.boxcoxinv","@stdlib/math/base/complex/abs":"base.cabs","@stdlib/math/base/complex/abs2":"base.cabs2","@stdlib/math/base/complex/add":"base.cadd","@stdlib/math/base/special/cbrt":"base.cbrt","@stdlib/math/base/complex/ceil":"base.cceil","@stdlib/math/base/complex/ceiln":"base.cceiln","@stdlib/math/base/complex/cis":"base.ccis","@stdlib/math/base/complex/divide":"base.cdiv","@stdlib/math/base/special/ceil":"base.ceil","@stdlib/math/base/special/ceil2":"base.ceil2","@stdlib/math/base/special/ceil10":"base.ceil10","@stdlib/math/base/special/ceilb":"base.ceilb","@stdlib/math/base/special/ceiln":"base.ceiln","@stdlib/math/base/special/ceilsd":"base.ceilsd","@stdlib/math/base/complex/exp":"base.cexp","@stdlib/math/base/complex/flipsign":"base.cflipsign","@stdlib/math/base/complex/floor":"base.cfloor","@stdlib/math/base/complex/floorn":"base.cfloorn","@stdlib/math/base/complex/inv":"base.cinv","@stdlib/math/base/special/clamp":"base.clamp","@stdlib/math/base/complex/multiply":"base.cmul","@stdlib/math/base/complex/negate":"base.cneg","@stdlib/math/base/tools/continued-fraction":"base.continuedFraction","@stdlib/math/base/special/copysign":"base.copysign","@stdlib/math/base/special/cos":"base.cos","@stdlib/math/base/special/cosh":"base.cosh","@stdlib/math/base/special/cosm1":"base.cosm1","@stdlib/math/base/special/cospi":"base.cospi","@stdlib/math/base/special/covercos":"base.covercos","@stdlib/math/base/special/coversin":"base.coversin","@stdlib/math/base/complex/phase":"base.cphase","@stdlib/math/base/complex/polar":"base.cpolar","@stdlib/math/base/complex/round":"base.cround","@stdlib/math/base/com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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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stdlib/utils/stack":"Stack","@stdlib/string/startcase":"startcase","@stdlib/string/starts-with":"startsWith","@stdlib/datasets/stopwords-en":"STOPWORDS_EN","@stdlib/array/to-strided-iterator":"stridedarray2iterator","@stdlib/streams/node/from-strided-array":"stridedArrayStream","@stdlib/buffer/from-string":"string2buffer","@stdlib/ndarray/sub2ind":"sub2ind","@stdlib/datasets/suthaharan-multi-hop-sensor-network":"SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","@stdlib/datasets/suthaharan-single-hop-sensor-network":"SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","@stdlib/symbol/ctor":"Symbol","@stdlib/utils/tabulate":"tabulate","@stdlib/utils/tabulate-by":"tabulateBy","@stdlib/utils/async/tabulate-by":"tabulateByAsync","@stdlib/time/tic":"tic","@stdlib/utils/timeit":"timeit","@stdlib/os/tmpdir":"tmpdir","@stdlib/time/toc":"toc","@stdlib/nlp/tokenize":"tokenize","@stdlib/streams/node/transform":"transformStream","@stdlib/string/trim":"trim","@stdlib/utils/try-catch":"trycatch","@stdlib/utils/async/try-catch":"trycatchAsync","@stdlib/utils/try-function":"tryFunction","@stdlib/utils/try-require":"tryRequire","@stdlib/utils/try-then":"trythen","@stdlib/utils/async/try-then":"trythenAsync","@stdlib/stats/ttest":"ttest","@stdlib/stats/ttest2":"ttest2","@stdlib/constants/math/float64-two-pi":"TWO_PI","@stdlib/array/typed":"typedarray","@stdlib/array/to-json":"typedarray2json","@stdlib/array/typed-complex-ctors":"typedarrayComplexCtors","@stdlib/array/typed-complex-dtypes":"typedarrayComplexDataTypes","@stdlib/array/typed-ctors":"typedarrayCtors","@stdlib/array/typed-dtypes":"typedarrayDataTypes","@stdlib/array/pool":"typedarraypool","@stdlib/utils/type-max":"typemax","@stdlib/utils/type-min":"typemin","@stdlib/utils/type-of":"typeOf","@stdlib/constants/math/uint8-max":"UINT8_MAX","@stdlib/constants/math/uint8-num-bytes":"UINT8_NUM_BYTES","@stdlib/array/uint8":"Uint8Array","@stdlib/array/uint8c":"Uint8ClampedArray","@stdlib/constants/math/uint16-max":"UINT16_MAX","@stdlib/constants/math/uint16-num-bytes":"UINT16_NUM_BYTES","@stdlib/array/uint16":"Uint16Array","@stdlib/constants/math/uint32-max":"UINT32_MAX","@stdlib/constants/math/uint32-num-bytes":"UINT32_NUM_BYTES","@stdlib/array/uint32":"Uint32Array","@stdlib/process/umask":"umask","@stdlib/string/uncapitalize":"uncapitalize","@stdlib/utils/uncapitalize-keys":"uncapitalizeKeys","@stdlib/utils/uncurry":"uncurry","@stdlib/utils/uncurry-right":"uncurryRight","@stdlib/constants/string/unicode-max":"UNICODE_MAX","@stdlib/constants/string/unicode-max-bmp":"UNICODE_MAX_BMP","@stdlib/plot/sparklines/unicode/column":"UnicodeColumnChartSparkline","@stdlib/plot/sparklines/unicode/line":"UnicodeLineChartSparkline","@stdlib/plot/sparklines/unicode":"UnicodeSparkline","@stdlib/plot/sparklines/unicode/tristate":"UnicodeTristateChartSparkline","@stdlib/plot/sparklines/unicode/up-down":"UnicodeUpDownChartSparkline","@stdlib/plot/sparklines/unicode/win-loss":"UnicodeWinLossChartSparkline","@stdlib/fs/unlink":"unlink","@stdlib/utils/unshift":"unshift","@stdlib/utils/until":"until","@stdlib/utils/async/until":"untilAsync","@stdlib/utils/until-each":"untilEach","@stdlib/utils/until-each-right":"untilEachRight","@stdlib/utils/unzip":"unzip","@stdlib/string/uppercase":"uppercase","@stdlib/utils/uppercase-keys":"uppercaseKeys","@stdlib/datasets/us-states-abbr":"US_STATES_ABBR","@stdlib/datasets/us-states-capitals":"US_STATES_CAPITALS","@stdlib/datasets/us-states-capitals-names":"US_STATES_CAPITALS_NAMES","@stdlib/datasets/us-states-names":"US_STATES_NAMES","@stdlib/datasets/us-states-names-capitals":"US_STATES_NAMES_CAPITALS","@stdlib/string/utf16-to-utf8-array":"utf16ToUTF8Array","@stdlib/stats/vartest":"vartest","@stdlib/utils/async/series-waterfall":"waterfall","@stdlib/utils/async/while":"whileAsync","@stdlib/utils/while-each":"whileEach","@stdlib/utils/while-each-right":"whileEachRight","@stdlib/utils/while":"whilst","@stdlib/utils/writable-properties":"writableProperties","@stdlib/utils/writable-properties-in":"writablePropertiesIn","@stdlib/utils/writable-property-names":"writablePropertyNames","@stdlib/utils/writable-property-names-in":"writablePropertyNamesIn","@stdlib/utils/writable-property-symbols":"writablePropertySymbols","@stdlib/utils/writable-property-symbols-in":"writablePropertySymbolsIn","@stdlib/fs/write-file":"writeFile","@stdlib/utils/zip":"zip","@stdlib/stats/ztest":"ztest","@stdlib/stats/ztest2":"ztest2"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv index 3400d364a337..0261677047af 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv @@ -1,7 +1,7 @@ "@stdlib/datasets/afinn-96","@stdlib/datasets/afinn-111" "@stdlib/datasets/afinn-111","@stdlib/datasets/afinn-96" "@stdlib/namespace/alias2pkg","@stdlib/namespace/alias2related,@stdlib/namespace/aliases,@stdlib/namespace/pkg2alias" -"@stdlib/namespace/alias2related","@stdlib/namespace/alias2pkg,@stdlib/namespace/aliases" +"@stdlib/namespace/alias2related","@stdlib/namespace/alias2pkg,@stdlib/namespace/aliases,@stdlib/namespace/pkg2related" "@stdlib/namespace/aliases","@stdlib/namespace/alias2pkg,@stdlib/namespace/alias2related,@stdlib/namespace/pkg2alias" "@stdlib/buffer/alloc-unsafe","@stdlib/buffer/ctor,@stdlib/buffer/from-array,@stdlib/buffer/from-arraybuffer,@stdlib/buffer/from-buffer,@stdlib/buffer/from-string" "@stdlib/stats/anova1","" @@ -1583,7 +1583,8 @@ "@stdlib/utils/pick","@stdlib/utils/pick-by" "@stdlib/utils/pick-by","@stdlib/utils/pick" "@stdlib/constants/math/float64-pinf","@stdlib/constants/math/float64-ninf" -"@stdlib/namespace/pkg2alias","@stdlib/namespace/alias2pkg,@stdlib/namespace/aliases" +"@stdlib/namespace/pkg2alias","@stdlib/namespace/alias2pkg,@stdlib/namespace/aliases,@stdlib/namespace/pkg2related" +"@stdlib/namespace/pkg2related","@stdlib/namespace/alias2related,@stdlib/namespace/aliases,@stdlib/namespace/pkg2alias" "@stdlib/os/platform","@stdlib/os/arch" "@stdlib/plot","@stdlib/plot/ctor" "@stdlib/plot/ctor","@stdlib/plot" diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.json index 022bf1bd6e5c..739046395016 100644 --- 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index de11f418a01f..8400cf07a75e 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -1601,6 +1601,7 @@ var db = { "pickBy": "function predicate( key, value ) {\n return ( value > 1 );\n};\nobj1 = { 'a': 1, 'b': 2 };\nobj2 = pickBy( obj1, predicate )\n", "PINF": "PINF\n", "pkg2alias": "v = pkg2alias( '@stdlib/math/base/special/sin' )\n", + "pkg2related": "v = pkg2related( '@stdlib/math/base/special/sin' )\n", "PLATFORM": "PLATFORM\n", "plot": "plot = plot()\n\n// Provide plot data at instantiation:\nx = [[0.10, 0.20, 0.30]];\ny = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n", "Plot": "plot = Plot()\n\n// Provide plot data at instantiation:\nx = [[0.10, 0.20, 0.30]];\ny = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n", diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index 51ade4c80780..c17d8853f68d 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -27,7 +27,7 @@ var db = { "AFINN_96": "\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n", "AFINN_111": "\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n", "alias2pkg": "\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n", - "alias2related": "\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases\n", + "alias2related": "\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n", "aliases": "\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n", "allocUnsafe": "\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n", "anova1": "\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n", @@ -1601,7 +1601,8 @@ var db = { "pick": "\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n", "pickBy": "\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n", "PINF": "\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n", - "pkg2alias": "\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n\n See Also\n --------\n alias2pkg, aliases\n", + "pkg2alias": "\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n", + "pkg2related": "\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n", "PLATFORM": "\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n", "plot": "\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n", "Plot": "\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n", From 182d47312d0e3a45d5f5d683318b9c8f10031e04 Mon Sep 17 00:00:00 2001 From: Planeshifter Date: Sat, 16 Mar 2019 13:50:02 -0400 Subject: [PATCH 065/142] Update comments and fix copy-paste error --- .../assert/is-absolute-path/docs/types/test.ts | 11 ++++------- .../assert/is-numeric-array/docs/types/index.d.ts | 1 - .../assert/is-relative-path/docs/types/test.ts | 9 ++++----- 3 files changed, 8 insertions(+), 13 deletions(-) diff --git a/lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/test.ts index 4657198ce269..74270c3e5c40 100644 --- a/lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/test.ts +++ b/lib/node_modules/@stdlib/assert/is-absolute-path/docs/types/test.ts @@ -33,28 +33,25 @@ import isAbsolutePath = require( './index' ); isAbsolutePath( 'C:\\foo\\bar\\baz', 123 ); // $ExpectError } -// Attached to main export is an posix method which returns a boolean... +// Attached to main export is a `posix` method which returns a boolean... { - // tslint:disable-next-line:no-construct isAbsolutePath.posix( '/foo/bar/baz' ); // $ExpectType boolean isAbsolutePath.posix( '/foo/../bar/baz' ); // $ExpectType boolean } -// The compiler throws an error if the posix method is provided an unsupported number of arguments... +// The compiler throws an error if the `posix` method is provided an unsupported number of arguments... { isAbsolutePath.posix(); // $ExpectError isAbsolutePath.posix( '/foo/../bar/baz', 123 ); // $ExpectError } - -// Attached to main export is an win32 method which returns a boolean... +// Attached to main export is a `win32` method which returns a boolean... { - // tslint:disable-next-line:no-construct isAbsolutePath.win32( 'foo\\bar\\baz' ); // $ExpectType boolean isAbsolutePath.win32( 'C:\\foo\\..\\bar\\baz' ); // $ExpectType boolean } -// The compiler throws an error if the win32 method is provided an unsupported number of arguments... +// The compiler throws an error if the `win32` method is provided an unsupported number of arguments... { isAbsolutePath.win32(); // $ExpectError isAbsolutePath.win32( 'C:\\foo\\..\\bar\\baz', 123 ); // $ExpectError diff --git a/lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/index.d.ts index 3093129cdef2..e8cf53b38a1c 100644 --- a/lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/assert/is-numeric-array/docs/types/index.d.ts @@ -18,7 +18,6 @@ // TypeScript Version: 2.0 - /** * Tests if a value is a numeric array. * diff --git a/lib/node_modules/@stdlib/assert/is-relative-path/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-relative-path/docs/types/test.ts index cde9ee76b5cd..ffc440205711 100644 --- a/lib/node_modules/@stdlib/assert/is-relative-path/docs/types/test.ts +++ b/lib/node_modules/@stdlib/assert/is-relative-path/docs/types/test.ts @@ -33,28 +33,27 @@ import isRelativePath = require( './index' ); isRelativePath( 'foo\\bar\\baz', 123 ); // $ExpectError } -// Attached to main export is an posix method which returns a boolean... +// Attached to main export is a `posix` method which returns a boolean... { // tslint:disable-next-line:no-construct isRelativePath.posix( './foo/bar/baz' ); // $ExpectType boolean isRelativePath.posix( '/foo/../bar/baz' ); // $ExpectType boolean } -// The compiler throws an error if the posix method is provided an unsupported number of arguments... +// The compiler throws an error if the `posix` method is provided an unsupported number of arguments... { isRelativePath.posix(); // $ExpectError isRelativePath.posix( '/foo/../bar/baz', 123 ); // $ExpectError } - -// Attached to main export is an win32 method which returns a boolean... +// Attached to main export is a `win32` method which returns a boolean... { // tslint:disable-next-line:no-construct isRelativePath.win32( 'foo\\bar\\baz' ); // $ExpectType boolean isRelativePath.win32( 'C:\\foo\\..\\bar\\baz' ); // $ExpectType boolean } -// The compiler throws an error if the win32 method is provided an unsupported number of arguments... +// The compiler throws an error if the `win32` method is provided an unsupported number of arguments... { isRelativePath.win32(); // $ExpectError isRelativePath.win32( 'C:\\foo\\..\\bar\\baz', 123 ); // $ExpectError From 49f9b1cd73f24e8453647c4ff45a3aeb27d3894d Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 12:44:29 -0700 Subject: [PATCH 066/142] Add utility to set a configurable read-only property --- .../README.md | 98 +++++++++++++++++++ .../benchmark/benchmark.js | 50 ++++++++++ .../docs/repl.txt | 28 ++++++ .../examples/index.js | 37 +++++++ .../lib/index.js | 47 +++++++++ .../lib/main.js | 58 +++++++++++ .../package.json | 68 +++++++++++++ .../test/test.js | 90 +++++++++++++++++ 8 files changed, 476 insertions(+) create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-property/README.md create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-property/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-property/examples/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-property/lib/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-property/lib/main.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-property/package.json create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-property/test/test.js diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/README.md b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/README.md new file mode 100644 index 000000000000..b63692ceabbc --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/README.md @@ -0,0 +1,98 @@ + + +# Configurable Read-Only + +> [Define][@stdlib/utils/define-property] a configurable **read-only** property. + +
+ +## Usage + +```javascript +var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); +``` + +#### setConfigurableReadOnly( obj, prop, value ) + +[Defines][@stdlib/utils/define-property] a configurable **read-only** property. + + + +```javascript +var obj = {}; + +setConfigurableReadOnly( obj, 'foo', 'bar' ); + +obj.foo = 'boop'; +// throws +``` + +
+ + + +
+ +## Notes + +- Configurable read-only properties are **enumerable**. + +
+ + + +
+ +## Examples + + + +```javascript +var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); + +function Foo( name ) { + if ( !(this instanceof Foo) ) { + return new Foo( name ); + } + setConfigurableReadOnly( this, 'name', name ); + return this; +} + +var foo = new Foo( 'beep' ); + +try { + foo.name = 'boop'; +} catch ( err ) { + console.error( err.message ); +} +``` + +
+ + + +
+ +[@stdlib/utils/define-property]: https://github.com/stdlib-js/stdlib + +
+ + diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/benchmark/benchmark.js b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/benchmark/benchmark.js new file mode 100644 index 000000000000..08d960edc1ad --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/benchmark/benchmark.js @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var fromCodePoint = require( '@stdlib/string/from-code-point' ); +var pkg = require( './../package.json' ).name; +var setConfigurableReadOnly = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var obj; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + obj = {}; + setConfigurableReadOnly( obj, 'foo', fromCodePoint( 97 + (i%26) ) ); + if ( !isString( obj.foo ) ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( obj.foo ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/repl.txt b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/repl.txt new file mode 100644 index 000000000000..12246a9053be --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/repl.txt @@ -0,0 +1,28 @@ + +{{alias}}( obj, prop, value ) + Defines a configurable read-only property. + + Configurable read-only properties are enumerable. + + Parameters + ---------- + obj: Object + Object on which to define the property. + + prop: string|symbol + Property name. + + value: any + Value to set. + + Examples + -------- + > var obj = {}; + > {{alias}}( obj, 'foo', 'bar' ); + > obj.foo = 'boop'; + > obj + { 'foo': 'bar' } + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/examples/index.js b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/examples/index.js new file mode 100644 index 000000000000..692122fddd7f --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var setConfigurableReadOnly = require( './../lib' ); + +function Foo( name ) { + if ( !(this instanceof Foo) ) { + return new Foo( name ); + } + setConfigurableReadOnly( this, 'name', name ); + return this; +} + +var foo = new Foo( 'beep' ); + +try { + foo.name = 'boop'; +} catch ( err ) { + console.error( err.message ); +} diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/lib/index.js b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/lib/index.js new file mode 100644 index 000000000000..81d63e81f98b --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/lib/index.js @@ -0,0 +1,47 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Define a configurable read-only property. +* +* @module @stdlib/utils/define-configurable-read-only-property +* +* @example +* var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); +* +* var obj = {}; +* +* setConfigurableReadOnly( obj, 'foo', 'bar' ); +* +* try { +* obj.foo = 'boop'; +* } catch ( err ) { +* console.error( err.message ); +* } +*/ + +// MODULES // + +var setConfigurableReadOnly = require( './main.js' ); + + +// EXPORTS // + +module.exports = setConfigurableReadOnly; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/lib/main.js b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/lib/main.js new file mode 100644 index 000000000000..653414a05969 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/lib/main.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var defineProperty = require( '@stdlib/utils/define-property' ); + + +// MAIN // + +/** +* Defines a configurable read-only property. +* +* @param {Object} obj - object on which to define the property +* @param {(string|symbol)} prop - property name +* @param {*} value - value to set +* +* @example +* var obj = {}; +* +* setConfigurableReadOnly( obj, 'foo', 'bar' ); +* +* try { +* obj.foo = 'boop'; +* } catch ( err ) { +* console.error( err.message ); +* } +*/ +function setConfigurableReadOnly( obj, prop, value ) { + defineProperty( obj, prop, { + 'configurable': true, + 'enumerable': true, + 'writable': false, + 'value': value + }); +} + + +// EXPORTS // + +module.exports = setConfigurableReadOnly; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/package.json b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/package.json new file mode 100644 index 000000000000..bc412a97b9fb --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/utils/define-configurable-read-only-property", + "version": "0.0.0", + "description": "Define a configurable read-only property.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdutils", + "stdutil", + "utilities", + "utility", + "utils", + "util", + "object", + "property", + "define", + "set", + "value", + "prop", + "read-only", + "writable", + "configurable" + ] +} diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/test/test.js b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/test/test.js new file mode 100644 index 000000000000..fa625dd74d43 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/test/test.js @@ -0,0 +1,90 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var objectKeys = require( '@stdlib/utils/keys' ); +var defineProperty = require( '@stdlib/utils/define-property' ); +var propertyDescriptor = require( '@stdlib/utils/property-descriptor' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var setConfigurableReadOnly = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.equal( typeof setConfigurableReadOnly, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function sets a property on a provided object', function test( t ) { + var obj = {}; + setConfigurableReadOnly( obj, 'foo', 'bar' ); + t.equal( obj.foo, 'bar', 'returns expected value' ); + t.end(); +}); + +tape( 'the read-only property is not writable', function test( t ) { + var obj = {}; + setConfigurableReadOnly( obj, 'foo', 'bar' ); + t.throws( foo, Error, 'property cannot be set' ); + t.end(); + + function foo() { + obj.foo = 'bip'; + } +}); + +tape( 'the read-only property is configurable', function test( t ) { + var desc; + var obj; + + obj = {}; + setConfigurableReadOnly( obj, 'foo', 'bar' ); + setConfigurableReadOnly( obj, 'beep', 'boop' ); + + desc = { + 'configurable': true, + 'enumerable': false, + 'writable': true, + 'value': 'buzz' + }; + defineProperty( obj, 'foo', desc ); + t.deepEqual( propertyDescriptor( obj, 'foo' ), desc, 'property can be reconfigured' ); + + t.equal( obj.beep, 'boop', 'returns expected value' ); + t.equal( hasOwnProp( obj, 'beep' ), true, 'has property' ); + + // Configurable properties can be deleted... + delete obj.beep; + t.equal( obj.beep, void 0, 'returns expected value' ); + t.equal( hasOwnProp( obj, 'beep' ), false, 'does not have property' ); + + t.end(); +}); + +tape( 'the read-only property is enumerable', function test( t ) { + var obj = {}; + setConfigurableReadOnly( obj, 'foo', 'bar' ); + t.deepEqual( objectKeys( obj ), [ 'foo' ], 'property is enumerable' ); + t.end(); +}); From c0b69cbe8fad93f472274263d0f52907116cc447 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 12:46:49 -0700 Subject: [PATCH 067/142] Update namespace --- lib/node_modules/@stdlib/utils/lib/index.js | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/lib/node_modules/@stdlib/utils/lib/index.js b/lib/node_modules/@stdlib/utils/lib/index.js index 4eac9d4bd255..d8e71ce7eab2 100644 --- a/lib/node_modules/@stdlib/utils/lib/index.js +++ b/lib/node_modules/@stdlib/utils/lib/index.js @@ -243,6 +243,15 @@ setReadOnly( utils, 'deepPluck', require( '@stdlib/utils/deep-pluck' ) ); */ setReadOnly( utils, 'deepSet', require( '@stdlib/utils/deep-set' ) ); +/** +* @name setConfigurableReadOnly +* @memberof utils +* @readonly +* @type {Function} +* @see {@link module:@stdlib/utils/define-configurable-read-only-property} +*/ +setReadOnly( utils, 'setConfigurableReadOnly', require( '@stdlib/utils/define-configurable-read-only-property' ) ); + /** * @name setNonEnumerableProperty * @memberof utils From 86b038ca0307d837e3606bc6d7d462ed4a90955f Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 12:50:54 -0700 Subject: [PATCH 068/142] Update namespace --- .../@stdlib/namespace/alias2pkg/data/data.csv | 1 + .../@stdlib/namespace/alias2pkg/data/data.json | 2 +- .../@stdlib/namespace/alias2related/data/data.csv | 1 + .../@stdlib/namespace/alias2related/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.txt | 1 + .../@stdlib/namespace/lib/namespace/s.js | 12 ++++++++++++ .../@stdlib/namespace/pkg2alias/data/data.csv | 1 + .../@stdlib/namespace/pkg2alias/data/data.json | 2 +- .../@stdlib/namespace/pkg2related/data/data.csv | 1 + .../@stdlib/namespace/pkg2related/data/data.json | 2 +- lib/node_modules/@stdlib/repl/code-blocks/lib/db.js | 1 + lib/node_modules/@stdlib/repl/help/lib/db.js | 1 + 13 files changed, 24 insertions(+), 5 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index 40a0b037cf33..dc96cb31280a 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1759,6 +1759,7 @@ SECONDS_IN_MINUTE,"@stdlib/constants/time/seconds-in-minute" SECONDS_IN_WEEK,"@stdlib/constants/time/seconds-in-week" secondsInMonth,"@stdlib/time/seconds-in-month" secondsInYear,"@stdlib/time/seconds-in-year" +setConfigurableReadOnly,"@stdlib/utils/define-configurable-read-only-property" setNonEnumerableProperty,"@stdlib/utils/define-nonenumerable-property" setNonEnumerableReadOnly,"@stdlib/utils/define-nonenumerable-read-only-property" setNonEnumerableReadOnlyAccessor,"@stdlib/utils/define-nonenumerable-read-only-accessor" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index 3b20f3bdcf60..0a468e0857a0 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ 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araswamy/variance","base.dists.laplace.cdf":"@stdlib/stats/base/dists/laplace/cdf","base.dists.laplace.entropy":"@stdlib/stats/base/dists/laplace/entropy","base.dists.laplace.kurtosis":"@stdlib/stats/base/dists/laplace/kurtosis","base.dists.laplace.Laplace":"@stdlib/stats/base/dists/laplace/ctor","base.dists.laplace.logcdf":"@stdlib/stats/base/dists/laplace/logcdf","base.dists.laplace.logpdf":"@stdlib/stats/base/dists/laplace/logpdf","base.dists.laplace.mean":"@stdlib/stats/base/dists/laplace/mean","base.dists.laplace.median":"@stdlib/stats/base/dists/laplace/median","base.dists.laplace.mgf":"@stdlib/stats/base/dists/laplace/mgf","base.dists.laplace.mode":"@stdlib/stats/base/dists/laplace/mode","base.dists.laplace.pdf":"@stdlib/stats/base/dists/laplace/pdf","base.dists.laplace.quantile":"@stdlib/stats/base/dists/laplace/quantile","base.dists.laplace.skewness":"@stdlib/stats/base/dists/laplace/skewness","base.dists.laplace.stdev":"@stdlib/stats/base/dists/laplace/stdev","base.dists.laplace.variance":"@stdlib/stats/base/dists/laplace/variance","base.dists.levy.cdf":"@stdlib/stats/base/dists/levy/cdf","base.dists.levy.entropy":"@stdlib/stats/base/dists/levy/entropy","base.dists.levy.Levy":"@stdlib/stats/base/dists/levy/ctor","base.dists.levy.logcdf":"@stdlib/stats/base/dists/levy/logcdf","base.dists.levy.logpdf":"@stdlib/stats/base/dists/levy/logpdf","base.dists.levy.mean":"@stdlib/stats/base/dists/levy/mean","base.dists.levy.median":"@stdlib/stats/base/dists/levy/median","base.dists.levy.mode":"@stdlib/stats/base/dists/levy/mode","base.dists.levy.pdf":"@stdlib/stats/base/dists/levy/pdf","base.dists.levy.quantile":"@stdlib/stats/base/dists/levy/quantile","base.dists.levy.stdev":"@stdlib/stats/base/dists/levy/stdev","base.dists.levy.variance":"@stdlib/stats/base/dists/levy/variance","base.dists.logistic.cdf":"@stdlib/stats/base/dists/logistic/cdf","base.dists.logistic.entropy":"@stdlib/stats/base/dists/logistic/entropy","base.dists.logistic.kurtosis":"@stdlib/stats/base/dists/logistic/kurtosis","base.dists.logistic.logcdf":"@stdlib/stats/base/dists/logistic/logcdf","base.dists.logistic.Logistic":"@stdlib/stats/base/dists/logistic/ctor","base.dists.logistic.logpdf":"@stdlib/stats/base/dists/logistic/logpdf","base.dists.logistic.mean":"@stdlib/stats/base/dists/logistic/mean","base.dists.logistic.median":"@stdlib/stats/base/dists/logistic/median","base.dists.logistic.mgf":"@stdlib/stats/base/dists/logistic/mgf","base.dists.logistic.mode":"@stdlib/stats/base/dists/logistic/mode","base.dists.logistic.pdf":"@stdlib/stats/base/dists/logistic/pdf","base.dists.logistic.quantile":"@stdlib/stats/base/dists/logistic/quantile","base.dists.logistic.skewness":"@stdlib/stats/base/dists/logistic/skewness","base.dists.logistic.stdev":"@stdlib/stats/base/dists/logistic/stdev","base.dists.logistic.variance":"@stdlib/stats/base/dists/logistic/variance","base.dists.lognormal.cdf":"@stdlib/stats/base/dists/lognormal/cdf","base.dists.lognormal.entropy":"@stdlib/stats/base/dists/lognormal/entropy","base.dists.lognormal.kurtosis":"@stdlib/stats/base/dists/lognormal/kurtosis","base.dists.lognormal.LogNormal":"@stdlib/stats/base/dists/lognormal/ctor","base.dists.lognormal.logpdf":"@stdlib/stats/base/dists/lognormal/logpdf","base.dists.lognormal.mean":"@stdlib/stats/base/dists/lognormal/mean","base.dists.lognormal.median":"@stdlib/stats/base/dists/lognormal/median","base.dists.lognormal.mode":"@stdlib/stats/base/dists/lognormal/mode","base.dists.lognormal.pdf":"@stdlib/stats/base/dists/lognormal/pdf","base.dists.lognormal.quantile":"@stdlib/stats/base/dists/lognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdli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araswamy/variance","base.dists.laplace.cdf":"@stdlib/stats/base/dists/laplace/cdf","base.dists.laplace.entropy":"@stdlib/stats/base/dists/laplace/entropy","base.dists.laplace.kurtosis":"@stdlib/stats/base/dists/laplace/kurtosis","base.dists.laplace.Laplace":"@stdlib/stats/base/dists/laplace/ctor","base.dists.laplace.logcdf":"@stdlib/stats/base/dists/laplace/logcdf","base.dists.laplace.logpdf":"@stdlib/stats/base/dists/laplace/logpdf","base.dists.laplace.mean":"@stdlib/stats/base/dists/laplace/mean","base.dists.laplace.median":"@stdlib/stats/base/dists/laplace/median","base.dists.laplace.mgf":"@stdlib/stats/base/dists/laplace/mgf","base.dists.laplace.mode":"@stdlib/stats/base/dists/laplace/mode","base.dists.laplace.pdf":"@stdlib/stats/base/dists/laplace/pdf","base.dists.laplace.quantile":"@stdlib/stats/base/dists/laplace/quantile","base.dists.laplace.skewness":"@stdlib/stats/base/dists/laplace/skewness","base.dists.laplace.stdev":"@stdlib/stats/base/dists/laplace/stdev","base.dists.laplace.variance":"@stdlib/stats/base/dists/laplace/variance","base.dists.levy.cdf":"@stdlib/stats/base/dists/levy/cdf","base.dists.levy.entropy":"@stdlib/stats/base/dists/levy/entropy","base.dists.levy.Levy":"@stdlib/stats/base/dists/levy/ctor","base.dists.levy.logcdf":"@stdlib/stats/base/dists/levy/logcdf","base.dists.levy.logpdf":"@stdlib/stats/base/dists/levy/logpdf","base.dists.levy.mean":"@stdlib/stats/base/dists/levy/mean","base.dists.levy.median":"@stdlib/stats/base/dists/levy/median","base.dists.levy.mode":"@stdlib/stats/base/dists/levy/mode","base.dists.levy.pdf":"@stdlib/stats/base/dists/levy/pdf","base.dists.levy.quantile":"@stdlib/stats/base/dists/levy/quantile","base.dists.levy.stdev":"@stdlib/stats/base/dists/levy/stdev","base.dists.levy.variance":"@stdlib/stats/base/dists/levy/variance","base.dists.logistic.cdf":"@stdlib/stats/base/dists/logistic/cdf","base.dists.logistic.entropy":"@stdlib/stats/base/dists/logistic/entropy","base.dists.logistic.kurtosis":"@stdlib/stats/base/dists/logistic/kurtosis","base.dists.logistic.logcdf":"@stdlib/stats/base/dists/logistic/logcdf","base.dists.logistic.Logistic":"@stdlib/stats/base/dists/logistic/ctor","base.dists.logistic.logpdf":"@stdlib/stats/base/dists/logistic/logpdf","base.dists.logistic.mean":"@stdlib/stats/base/dists/logistic/mean","base.dists.logistic.median":"@stdlib/stats/base/dists/logistic/median","base.dists.logistic.mgf":"@stdlib/stats/base/dists/logistic/mgf","base.dists.logistic.mode":"@stdlib/stats/base/dists/logistic/mode","base.dists.logistic.pdf":"@stdlib/stats/base/dists/logistic/pdf","base.dists.logistic.quantile":"@stdlib/stats/base/dists/logistic/quantile","base.dists.logistic.skewness":"@stdlib/stats/base/dists/logistic/skewness","base.dists.logistic.stdev":"@stdlib/stats/base/dists/logistic/stdev","base.dists.logistic.variance":"@stdlib/stats/base/dists/logistic/variance","base.dists.lognormal.cdf":"@stdlib/stats/base/dists/lognormal/cdf","base.dists.lognormal.entropy":"@stdlib/stats/base/dists/lognormal/entropy","base.dists.lognormal.kurtosis":"@stdlib/stats/base/dists/lognormal/kurtosis","base.dists.lognormal.LogNormal":"@stdlib/stats/base/dists/lognormal/ctor","base.dists.lognormal.logpdf":"@stdlib/stats/base/dists/lognormal/logpdf","base.dists.lognormal.mean":"@stdlib/stats/base/dists/lognormal/mean","base.dists.lognormal.median":"@stdlib/stats/base/dists/lognormal/median","base.dists.lognormal.mode":"@stdlib/stats/base/dists/lognormal/mode","base.dists.lognormal.pdf":"@stdlib/stats/base/dists/lognormal/pdf","base.dists.lognormal.quantile":"@stdlib/stats/base/dists/lognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdli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h/float64-sqrt-two","SQRT_TWO_PI":"@stdlib/constants/math/float64-sqrt-two-pi","Stack":"@stdlib/utils/stack","startcase":"@stdlib/string/startcase","startsWith":"@stdlib/string/starts-with","STOPWORDS_EN":"@stdlib/datasets/stopwords-en","stridedarray2iterator":"@stdlib/array/to-strided-iterator","stridedArrayStream":"@stdlib/streams/node/from-strided-array","string2buffer":"@stdlib/buffer/from-string","sub2ind":"@stdlib/ndarray/sub2ind","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-multi-hop-sensor-network","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-single-hop-sensor-network","Symbol":"@stdlib/symbol/ctor","tabulate":"@stdlib/utils/tabulate","tabulateBy":"@stdlib/utils/tabulate-by","tabulateByAsync":"@stdlib/utils/async/tabulate-by","tic":"@stdlib/time/tic","timeit":"@stdlib/utils/timeit","tmpdir":"@stdlib/os/tmpdir","toc":"@stdlib/time/toc","tokenize":"@stdlib/nlp/tokenize","transformStream":"@stdlib/streams/node/transform","trim":"@stdlib/string/trim","trycatch":"@stdlib/utils/try-catch","trycatchAsync":"@stdlib/utils/async/try-catch","tryFunction":"@stdlib/utils/try-function","tryRequire":"@stdlib/utils/try-require","trythen":"@stdlib/utils/try-then","trythenAsync":"@stdlib/utils/async/try-then","ttest":"@stdlib/stats/ttest","ttest2":"@stdlib/stats/ttest2","TWO_PI":"@stdlib/constants/math/float64-two-pi","typedarray":"@stdlib/array/typed","typedarray2json":"@stdlib/array/to-json","typedarrayComplexCtors":"@stdlib/array/typed-complex-ctors","typedarrayComplexDataTypes":"@stdlib/array/typed-complex-dtypes","typedarrayCtors":"@stdlib/array/typed-ctors","typedarrayDataTypes":"@stdlib/array/typed-dtypes","typedarraypool":"@stdlib/array/pool","typemax":"@stdlib/utils/type-max","typemin":"@stdlib/utils/type-min","typeOf":"@stdlib/utils/type-of","UINT8_MAX":"@stdlib/constants/math/uint8-max","UINT8_NUM_BYTES":"@stdlib/constants/math/uint8-num-bytes","Uint8Array":"@stdlib/array/uint8","Uint8ClampedArray":"@stdlib/array/uint8c","UINT16_MAX":"@stdlib/constants/math/uint16-max","UINT16_NUM_BYTES":"@stdlib/constants/math/uint16-num-bytes","Uint16Array":"@stdlib/array/uint16","UINT32_MAX":"@stdlib/constants/math/uint32-max","UINT32_NUM_BYTES":"@stdlib/constants/math/uint32-num-bytes","Uint32Array":"@stdlib/array/uint32","umask":"@stdlib/process/umask","uncapitalize":"@stdlib/string/uncapitalize","uncapitalizeKeys":"@stdlib/utils/uncapitalize-keys","uncurry":"@stdlib/utils/uncurry","uncurryRight":"@stdlib/utils/uncurry-right","UNICODE_MAX":"@stdlib/constants/string/unicode-max","UNICODE_MAX_BMP":"@stdlib/constants/string/unicode-max-bmp","UnicodeColumnChartSparkline":"@stdlib/plot/sparklines/unicode/column","UnicodeLineChartSparkline":"@stdlib/plot/sparklines/unicode/line","UnicodeSparkline":"@stdlib/plot/sparklines/unicode","UnicodeTristateChartSparkline":"@stdlib/plot/sparklines/unicode/tristate","UnicodeUpDownChartSparkline":"@stdlib/plot/sparklines/unicode/up-down","UnicodeWinLossChartSparkline":"@stdlib/plot/sparklines/unicode/win-loss","unlink":"@stdlib/fs/unlink","unshift":"@stdlib/utils/unshift","until":"@stdlib/utils/until","untilAsync":"@stdlib/utils/async/until","untilEach":"@stdlib/utils/until-each","untilEachRight":"@stdlib/utils/until-each-right","unzip":"@stdlib/utils/unzip","uppercase":"@stdlib/string/uppercase","uppercaseKeys":"@stdlib/utils/uppercase-keys","US_STATES_ABBR":"@stdlib/datasets/us-states-abbr","US_STATES_CAPITALS":"@stdlib/datasets/us-states-capitals","US_STATES_CAPITALS_NAMES":"@stdlib/datasets/us-states-capitals-names","US_STATES_NAMES":"@stdlib/datasets/us-states-names","US_STATES_NAMES_CAPITALS":"@stdlib/datasets/us-states-names-capitals","utf16ToUTF8Array":"@stdlib/string/utf16-to-utf8-array","vartest":"@stdlib/stats/vartest","waterfall":"@stdlib/utils/async/series-waterfall","whileAsync":"@stdlib/utils/async/while","whileEach":"@stdlib/utils/while-each","whileEachRight":"@stdlib/utils/while-each-right","whilst":"@stdlib/utils/while","writableProperties":"@stdlib/utils/writable-properties","writablePropertiesIn":"@stdlib/utils/writable-properties-in","writablePropertyNames":"@stdlib/utils/writable-property-names","writablePropertyNamesIn":"@stdlib/utils/writable-property-names-in","writablePropertySymbols":"@stdlib/utils/writable-property-symbols","writablePropertySymbolsIn":"@stdlib/utils/writable-property-symbols-in","writeFile":"@stdlib/fs/write-file","zip":"@stdlib/utils/zip","ztest":"@stdlib/stats/ztest","ztest2":"@stdlib/stats/ztest2"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv index 1245afd008de..930537bda3a1 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv @@ -1759,6 +1759,7 @@ SECONDS_IN_MINUTE,"" SECONDS_IN_WEEK,"" secondsInMonth,"secondsInYear" secondsInYear,"secondsInMonth" +setConfigurableReadOnly,"defineProperty,setReadOnly" setNonEnumerableProperty,"setNonEnumerableReadOnlyAccessor,setNonEnumerableReadOnly,setNonEnumerableReadWriteAccessor,setNonEnumerableWriteOnlyAccessor,setReadOnly" setNonEnumerableReadOnly,"setNonEnumerableProperty,setNonEnumerableReadOnlyAccessor,setNonEnumerableReadWriteAccessor,setNonEnumerableWriteOnlyAccessor,setReadOnly" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index db66ada82290..c57728e08332 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1759,6 +1759,7 @@ SECONDS_IN_MINUTE SECONDS_IN_WEEK secondsInMonth secondsInYear +setConfigurableReadOnly setNonEnumerableProperty setNonEnumerableReadOnly setNonEnumerableReadOnlyAccessor diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/s.js b/lib/node_modules/@stdlib/namespace/lib/namespace/s.js index cd5ace0ec45b..f8195385d2b7 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/s.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/s.js @@ -166,6 +166,18 @@ ns.push({ ] }); +ns.push({ + 'alias': 'setConfigurableReadOnly', + 'path': '@stdlib/utils/define-configurable-read-only-property', + 'value': require( '@stdlib/utils/define-configurable-read-only-property' ), + 'type': 'Function', + 'related': [ + '@stdlib/utils/define-configurable-read-only-accessor', + '@stdlib/utils/define-property', + '@stdlib/utils/define-read-only-property' + ] +}); + ns.push({ 'alias': 'setNonEnumerableProperty', 'path': '@stdlib/utils/define-nonenumerable-property', diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index 17eaa8f4b428..edb1806bec3c 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -1759,6 +1759,7 @@ "@stdlib/constants/time/seconds-in-week",SECONDS_IN_WEEK "@stdlib/time/seconds-in-month",secondsInMonth "@stdlib/time/seconds-in-year",secondsInYear +"@stdlib/utils/define-configurable-read-only-property",setConfigurableReadOnly "@stdlib/utils/define-nonenumerable-property",setNonEnumerableProperty "@stdlib/utils/define-nonenumerable-read-only-property",setNonEnumerableReadOnly "@stdlib/utils/define-nonenumerable-read-only-accessor",setNonEnumerableReadOnlyAccessor diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index 9bdbab1e9e66..22e754e9230c 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ 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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv index 0261677047af..cc3bd6f30355 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv @@ -1759,6 +1759,7 @@ "@stdlib/constants/time/seconds-in-week","" "@stdlib/time/seconds-in-month","@stdlib/time/seconds-in-year" "@stdlib/time/seconds-in-year","@stdlib/time/seconds-in-month" +"@stdlib/utils/define-configurable-read-only-property","@stdlib/utils/define-property,@stdlib/utils/define-read-only-property" "@stdlib/utils/define-nonenumerable-property","@stdlib/utils/define-nonenumerable-read-only-accessor,@stdlib/utils/define-nonenumerable-read-only-property,@stdlib/utils/define-nonenumerable-read-write-accessor,@stdlib/utils/define-nonenumerable-write-only-accessor,@stdlib/utils/define-read-only-property" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index 8400cf07a75e..446469f35c84 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -1776,6 +1776,7 @@ var db = { "SECONDS_IN_WEEK": "wks = 3.14;\nsecs = wks * SECONDS_IN_WEEK\n", "secondsInMonth": "num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n", "secondsInYear": "num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n", + "setConfigurableReadOnly": "obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", "setNonEnumerableProperty": "obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n", "setNonEnumerableReadOnly": "obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", "setNonEnumerableReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index c17d8853f68d..aa30bd2bd9d3 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -1777,6 +1777,7 @@ var db = { "SECONDS_IN_WEEK": "\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n", "secondsInMonth": "\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n", "secondsInYear": "\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n", + "setConfigurableReadOnly": "\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperty, setReadOnly\n", "setNonEnumerableProperty": "\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", "setNonEnumerableReadOnly": "\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", "setNonEnumerableReadOnlyAccessor": "\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n", From 8223567ca3a5bb69a94134c48ce011d1dd7c5e07 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 13:39:53 -0700 Subject: [PATCH 069/142] Add object types --- lib/node_modules/@stdlib/types/index.d.ts | 110 +++++++++++++++++++ lib/node_modules/@stdlib/types/test.ts | 128 ++++++++++++++++++++++ 2 files changed, 238 insertions(+) diff --git a/lib/node_modules/@stdlib/types/index.d.ts b/lib/node_modules/@stdlib/types/index.d.ts index ebc0eb60f56e..9330d424eca2 100644 --- a/lib/node_modules/@stdlib/types/index.d.ts +++ b/lib/node_modules/@stdlib/types/index.d.ts @@ -163,6 +163,116 @@ declare module '@stdlib/types/iter' { } } +/** +* Module containing object definitions. +* +* @example +* import * as obj from `@stdlib/types/object`; +* +* const desc: obj.DataPropertyDescriptor = { +* 'configurable': false, +* 'enumerable': true, +* 'writable': false, +* 'value': 'beep' +* }; +* +* @example +* import { DataPropertyDescriptor } from `@stdlib/types/object`; +* +* const desc: DataPropertyDescriptor = { +* 'configurable': false, +* 'enumerable': true, +* 'writable': false, +* 'value': 'beep' +* }; +*/ +declare module '@stdlib/types/object' { + /** + * Interface describing a data property descriptor object. + * + * @example + * const desc: DataPropertyDescriptor = { + * 'configurable': false, + * 'enumerable': true, + * 'writable': false, + * 'value': 'beep' + * }; + */ + interface DataPropertyDescriptor { + /** + * Specifies whether a property descriptor may be changed and whether a property may be deleted from a corresponding object (default: `false`). + */ + configurable?: boolean; + + /** + * Specifies whether a property can be enumerated (default: `false`). + */ + enumerable?: boolean; + + /** + * Specifies whether the value associated with a property can be changed via the assignment operator (default: `false`). + */ + writable?: boolean; + + /** + * Value associated with a property (default: `undefined`). + */ + value?: any; + } + + /** + * Interface describing an accessor property descriptor object. + * + * @example + * const desc: AccessorPropertyDescriptor = { + * 'configurable': false, + * 'enumerable': true, + * 'get': (): string => 'foo', + * 'set': () => { throw new Error( 'invalid operation.' ); } + * }; + */ + interface AccessorPropertyDescriptor { + /** + * Specifies whether a property descriptor may be changed and whether a property may be deleted from a corresponding object (default: `false`). + */ + configurable?: boolean; + + /** + * Specifies whether a property can be enumerated (default: `false`). + */ + enumerable?: boolean; + + /** + * A function which serves as a getter for the property. + * + * ## Notes + * + * - If omitted from a descriptor, a property value cannot be accessed. + * - When the property is accessed, the function is called without arguments and with `this` set to the object through which the property is accessed (note: this may **not** be the object on which the property is defined due to inheritance). + * - The return value will be used as the value of the property. + */ + get?(): any; + + /** + * A function which serves as a setter for the property. + * + * ## Notes + * + * - If omitted from a descriptor, a property value cannot be assigned. + * - When the property is assigned to, the function is called with one argument (the value being assigned to the property) and with `this` set to the object through which the property is assigned. + */ + set?( x: any ): void; + } + + /** + * An object property name. + * + * @example + * const prop: PropertyName = 'foo'; + */ + type PropertyName = string | symbol; +} + /** * Module containing PRNG definitions. * diff --git a/lib/node_modules/@stdlib/types/test.ts b/lib/node_modules/@stdlib/types/test.ts index 9fca485a4b44..a597d1b72866 100644 --- a/lib/node_modules/@stdlib/types/test.ts +++ b/lib/node_modules/@stdlib/types/test.ts @@ -20,6 +20,7 @@ import * as array from '@stdlib/types/array'; import * as iter from '@stdlib/types/iter'; +import * as object from '@stdlib/types/object'; import * as random from '@stdlib/types/random'; /** @@ -142,6 +143,133 @@ function createIterableIterator(): iter.IterableIterator { createIterableIterator(); } +// The compiler should not throw an error when using object types... +{ + const desc1: object.DataPropertyDescriptor = { + 'configurable': true, + 'enumerable': false, + 'writable': false, + 'value': 'beep' + }; + if ( desc1.value !== 'beep' ) { + throw new Error( 'something went wrong' ); + }const desc2: object.DataPropertyDescriptor = { + 'enumerable': false, + 'writable': false, + 'value': 'beep' + }; + if ( desc2.value !== 'beep' ) { + throw new Error( 'something went wrong' ); + } + + const desc3: object.DataPropertyDescriptor = { + 'configurable': true, + 'writable': false, + 'value': 'beep' + }; + if ( desc3.value !== 'beep' ) { + throw new Error( 'something went wrong' ); + } + + const desc4: object.DataPropertyDescriptor = { + 'configurable': true, + 'enumerable': false, + 'writable': false + }; + if ( desc4.value ) { + throw new Error( 'something went wrong' ); + } + + const desc5: object.DataPropertyDescriptor = { + 'writable': false, + 'value': 'beep' + }; + if ( desc5.value !== 'beep' ) { + throw new Error( 'something went wrong' ); + } + + const desc6: object.DataPropertyDescriptor = { + 'configurable': true, + 'value': 'beep' + }; + if ( desc6.value !== 'beep' ) { + throw new Error( 'something went wrong' ); + } + + const desc7: object.DataPropertyDescriptor = { + 'enumerable': false, + 'value': 'beep' + }; + if ( desc7.value !== 'beep' ) { + throw new Error( 'something went wrong' ); + } + + const desc8: object.DataPropertyDescriptor = { + 'enumerable': false, + 'writable': false + }; + if ( desc8.value ) { + throw new Error( 'something went wrong' ); + } + + const desc9: object.AccessorPropertyDescriptor = { + 'configurable': true, + 'enumerable': false, + 'get': (): string => 'beep', + 'set': () => { throw new Error( 'beep' ); } + }; + if ( desc9.enumerable !== false ) { + throw new Error( 'something went wrong' ); + }const desc10: object.AccessorPropertyDescriptor = { + 'enumerable': false, + 'get': (): string => 'beep', + 'set': () => { throw new Error( 'beep' ); } + }; + if ( desc10.enumerable !== false ) { + throw new Error( 'something went wrong' ); + } + + const desc11: object.AccessorPropertyDescriptor = { + 'configurable': true, + 'get': (): string => 'beep', + 'set': () => { throw new Error( 'beep' ); } + }; + if ( desc11.enumerable !== false ) { + throw new Error( 'something went wrong' ); + } + + const desc12: object.AccessorPropertyDescriptor = { + 'configurable': true, + 'enumerable': false, + 'set': () => { throw new Error( 'beep' ); } + }; + if ( desc12.enumerable !== false ) { + throw new Error( 'something went wrong' ); + } + + const desc13: object.AccessorPropertyDescriptor = { + 'configurable': true, + 'enumerable': false, + 'get': (): string => 'beep' + }; + if ( desc13.enumerable !== false ) { + throw new Error( 'something went wrong' ); + } + + const desc14: object.AccessorPropertyDescriptor = { + 'get': (): string => 'beep', + 'set': () => { throw new Error( 'beep' ); } + }; + if ( desc14.enumerable !== false ) { + throw new Error( 'something went wrong' ); + } + + const prop: object.PropertyName = 'foo'; + if ( prop !== 'foo' ) { + throw new Error( 'something went wrong' ); + } +} + // The compiler should not throw an error when using PRNG types... { const rand: random.PRNG = (): number => 3.14; From 0a391aeae0d9cd596b79f4165cfe7282f5cfb78e Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 14:00:44 -0700 Subject: [PATCH 070/142] Add property descriptor type --- lib/node_modules/@stdlib/types/index.d.ts | 13 +++++++++++++ lib/node_modules/@stdlib/types/test.ts | 18 ++++++++++++++++-- 2 files changed, 29 insertions(+), 2 deletions(-) diff --git a/lib/node_modules/@stdlib/types/index.d.ts b/lib/node_modules/@stdlib/types/index.d.ts index 9330d424eca2..3da6f0f305b5 100644 --- a/lib/node_modules/@stdlib/types/index.d.ts +++ b/lib/node_modules/@stdlib/types/index.d.ts @@ -264,6 +264,19 @@ declare module '@stdlib/types/object' { set?( x: any ): void; } + /** + * Property descriptor object. + * + * @example + * const desc: PropertyDescriptor = { + * 'configurable': false, + * 'enumerable': true, + * 'writable': false, + * 'value': 'beep' + * }; + */ + type PropertyDescriptor = DataPropertyDescriptor | AccessorPropertyDescriptor; // tslint:disable-line:max-line-length + /** * An object property name. * diff --git a/lib/node_modules/@stdlib/types/test.ts b/lib/node_modules/@stdlib/types/test.ts index a597d1b72866..d90d34f3a436 100644 --- a/lib/node_modules/@stdlib/types/test.ts +++ b/lib/node_modules/@stdlib/types/test.ts @@ -153,7 +153,9 @@ function createIterableIterator(): iter.IterableIterator { }; if ( desc1.value !== 'beep' ) { throw new Error( 'something went wrong' ); - }const desc2: object.DataPropertyDescriptor = { + } + + const desc2: object.DataPropertyDescriptor = { 'enumerable': false, 'writable': false, 'value': 'beep' @@ -220,7 +222,9 @@ function createIterableIterator(): iter.IterableIterator { }; if ( desc9.enumerable !== false ) { throw new Error( 'something went wrong' ); - }const desc10: object.AccessorPropertyDescriptor = { + } + + const desc10: object.AccessorPropertyDescriptor = { 'enumerable': false, 'get': (): string => 'beep', 'set': () => { throw new Error( 'beep' ); } @@ -264,6 +268,16 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } + const desc15: object.PropertyDescriptor = { + 'configurable': true, + 'enumerable': false, + 'writable': false, + 'value': 'beep' + }; + if ( desc15.value !== 'beep' ) { + throw new Error( 'something went wrong' ); + } + const prop: object.PropertyName = 'foo'; if ( prop !== 'foo' ) { throw new Error( 'something went wrong' ); From 293a4ec10452958eec806e9c31dd5b02d48c9b5f Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 14:19:19 -0700 Subject: [PATCH 071/142] Add TypeScript declaration file --- .../docs/types/index.d.ts | 52 +++++++++++++++++++ .../docs/types/test.ts | 45 ++++++++++++++++ 2 files changed, 97 insertions(+) create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/types/test.ts diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/types/index.d.ts b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/types/index.d.ts new file mode 100644 index 000000000000..c83950086f4c --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/// + +import { PropertyName } from '@stdlib/types/object'; + +/** +* Defines a configurable read-only property. +* +* ## Notes +* +* - Configurable read-only properties are **enumerable**. +* +* @param obj - object on which to define property +* @param prop - property name +* @param value - value to set +* +* @example +* var obj = {}; +* +* setConfigurableReadOnly( obj, 'foo', 'bar' ); +* +* try { +* obj.foo = 'boop'; +* } catch ( err ) { +* console.error( err.message ); +* } +*/ +declare function setConfigurableReadOnly( obj: any, prop: PropertyName, value: any ): void; // tslint:disable-line: max-line-length + + +// EXPORTS // + +export = setConfigurableReadOnly; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/types/test.ts b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/types/test.ts new file mode 100644 index 000000000000..db23bbb5cb05 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/docs/types/test.ts @@ -0,0 +1,45 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import setConfigurableReadOnly = require( './index' ); + + +// TESTS // + +// The function returns `undefined`... +{ + setConfigurableReadOnly( {}, 'foo', 'bar' ); // $ExpectType void +} + +// The compiler throws an error if the function is provided a second argument which is not a valid property name... +{ + setConfigurableReadOnly( {}, true, 'bar' ); // $ExpectError + setConfigurableReadOnly( {}, false, 'bar' ); // $ExpectError + setConfigurableReadOnly( {}, null, 'bar' ); // $ExpectError + setConfigurableReadOnly( {}, undefined, 'bar' ); // $ExpectError + setConfigurableReadOnly( {}, [], 'bar' ); // $ExpectError + setConfigurableReadOnly( {}, {}, 'bar' ); // $ExpectError + setConfigurableReadOnly( {}, ( x: number ): number => x, 'bar' ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + setConfigurableReadOnly(); // $ExpectError + setConfigurableReadOnly( {} ); // $ExpectError + setConfigurableReadOnly( {}, 'foo' ); // $ExpectError +} From 267aaa18d09adf09938e24121b485d4ca98c0a7d Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 14:19:37 -0700 Subject: [PATCH 072/142] Rename import to avoid collision with TypeScript type --- lib/node_modules/@stdlib/types/test.ts | 34 +++++++++++++------------- 1 file changed, 17 insertions(+), 17 deletions(-) diff --git a/lib/node_modules/@stdlib/types/test.ts b/lib/node_modules/@stdlib/types/test.ts index d90d34f3a436..b372a02941bb 100644 --- a/lib/node_modules/@stdlib/types/test.ts +++ b/lib/node_modules/@stdlib/types/test.ts @@ -20,7 +20,7 @@ import * as array from '@stdlib/types/array'; import * as iter from '@stdlib/types/iter'; -import * as object from '@stdlib/types/object'; +import * as obj from '@stdlib/types/object'; import * as random from '@stdlib/types/random'; /** @@ -145,7 +145,7 @@ function createIterableIterator(): iter.IterableIterator { // The compiler should not throw an error when using object types... { - const desc1: object.DataPropertyDescriptor = { + const desc1: obj.DataPropertyDescriptor = { 'configurable': true, 'enumerable': false, 'writable': false, @@ -155,7 +155,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc2: object.DataPropertyDescriptor = { + const desc2: obj.DataPropertyDescriptor = { 'enumerable': false, 'writable': false, 'value': 'beep' @@ -164,7 +164,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc3: object.DataPropertyDescriptor = { + const desc3: obj.DataPropertyDescriptor = { 'configurable': true, 'writable': false, 'value': 'beep' @@ -173,7 +173,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc4: object.DataPropertyDescriptor = { + const desc4: obj.DataPropertyDescriptor = { 'configurable': true, 'enumerable': false, 'writable': false @@ -182,7 +182,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc5: object.DataPropertyDescriptor = { + const desc5: obj.DataPropertyDescriptor = { 'writable': false, 'value': 'beep' }; @@ -190,7 +190,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc6: object.DataPropertyDescriptor = { + const desc6: obj.DataPropertyDescriptor = { 'configurable': true, 'value': 'beep' }; @@ -198,7 +198,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc7: object.DataPropertyDescriptor = { + const desc7: obj.DataPropertyDescriptor = { 'enumerable': false, 'value': 'beep' }; @@ -206,7 +206,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc8: object.DataPropertyDescriptor = { + const desc8: obj.DataPropertyDescriptor = { 'enumerable': false, 'writable': false }; @@ -214,7 +214,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc9: object.AccessorPropertyDescriptor = { + const desc9: obj.AccessorPropertyDescriptor = { 'configurable': true, 'enumerable': false, 'get': (): string => 'beep', @@ -224,7 +224,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc10: object.AccessorPropertyDescriptor = { + const desc10: obj.AccessorPropertyDescriptor = { 'enumerable': false, 'get': (): string => 'beep', 'set': () => { throw new Error( 'beep' ); } @@ -233,7 +233,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc11: object.AccessorPropertyDescriptor = { + const desc11: obj.AccessorPropertyDescriptor = { 'configurable': true, 'get': (): string => 'beep', 'set': () => { throw new Error( 'beep' ); } @@ -242,7 +242,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc12: object.AccessorPropertyDescriptor = { + const desc12: obj.AccessorPropertyDescriptor = { 'configurable': true, 'enumerable': false, 'set': () => { throw new Error( 'beep' ); } @@ -251,7 +251,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc13: object.AccessorPropertyDescriptor = { + const desc13: obj.AccessorPropertyDescriptor = { 'configurable': true, 'enumerable': false, 'get': (): string => 'beep' @@ -260,7 +260,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc14: object.AccessorPropertyDescriptor = { + const desc14: obj.AccessorPropertyDescriptor = { 'get': (): string => 'beep', 'set': () => { throw new Error( 'beep' ); } }; @@ -268,7 +268,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const desc15: object.PropertyDescriptor = { + const desc15: obj.PropertyDescriptor = { 'configurable': true, 'enumerable': false, 'writable': false, @@ -278,7 +278,7 @@ function createIterableIterator(): iter.IterableIterator { throw new Error( 'something went wrong' ); } - const prop: object.PropertyName = 'foo'; + const prop: obj.PropertyName = 'foo'; if ( prop !== 'foo' ) { throw new Error( 'something went wrong' ); } From fefec52268755390578aaccee4444b381f011ffa Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 15:12:06 -0700 Subject: [PATCH 073/142] Fix variable name --- .../test/test.js | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/lib/node_modules/@stdlib/utils/define-nonenumerable-read-only-accessor/test/test.js b/lib/node_modules/@stdlib/utils/define-nonenumerable-read-only-accessor/test/test.js index d825f126d32e..406e04e20a69 100644 --- a/lib/node_modules/@stdlib/utils/define-nonenumerable-read-only-accessor/test/test.js +++ b/lib/node_modules/@stdlib/utils/define-nonenumerable-read-only-accessor/test/test.js @@ -23,20 +23,20 @@ var tape = require( 'tape' ); var objectKeys = require( '@stdlib/utils/keys' ); var defineProperty = require( '@stdlib/utils/define-property' ); -var setNonEnumerableeadOnlyAccessor = require( './../lib' ); // eslint-disable-line id-length +var setNonEnumerableReadOnlyAccessor = require( './../lib' ); // eslint-disable-line id-length // TESTS // tape( 'main export is a function', function test( t ) { t.ok( true, __filename ); - t.equal( typeof setNonEnumerableeadOnlyAccessor, 'function', 'main export is a function' ); + t.equal( typeof setNonEnumerableReadOnlyAccessor, 'function', 'main export is a function' ); t.end(); }); tape( 'the function sets a property on a provided object', function test( t ) { var obj = {}; - setNonEnumerableeadOnlyAccessor( obj, 'foo', getter ); + setNonEnumerableReadOnlyAccessor( obj, 'foo', getter ); t.equal( obj.foo, 'bar', 'returns expected value' ); t.end(); @@ -47,7 +47,7 @@ tape( 'the function sets a property on a provided object', function test( t ) { tape( 'the read-only property is not writable', function test( t ) { var obj = {}; - setNonEnumerableeadOnlyAccessor( obj, 'foo', getter ); + setNonEnumerableReadOnlyAccessor( obj, 'foo', getter ); t.throws( foo, Error, 'property cannot be set' ); t.end(); @@ -62,7 +62,7 @@ tape( 'the read-only property is not writable', function test( t ) { tape( 'the read-only property is not configurable', function test( t ) { var obj = {}; - setNonEnumerableeadOnlyAccessor( obj, 'foo', getter ); + setNonEnumerableReadOnlyAccessor( obj, 'foo', getter ); t.throws( foo, Error, 'property cannot be deleted' ); t.throws( bar, Error, 'property cannot be reconfigured' ); t.end(); @@ -86,7 +86,7 @@ tape( 'the read-only property is not configurable', function test( t ) { tape( 'the read-only property is not enumerable', function test( t ) { var obj = {}; - setNonEnumerableeadOnlyAccessor( obj, 'foo', getter ); + setNonEnumerableReadOnlyAccessor( obj, 'foo', getter ); t.equal( objectKeys( obj ).length, 0, 'property is not enumerable' ); t.end(); From 0dad968423ce52b9fc62a4e70e63b4df3a33e721 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 15:12:42 -0700 Subject: [PATCH 074/142] Fix missing `types` field --- .../utils/define-configurable-read-only-property/package.json | 1 + 1 file changed, 1 insertion(+) diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/package.json b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/package.json index bc412a97b9fb..a72d08a61cd2 100644 --- a/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/package.json +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-property/package.json @@ -21,6 +21,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { From 1b09094883c1dc3592851c16d7998ee45c996bcd Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 15:24:38 -0700 Subject: [PATCH 075/142] Add utility to define a configurable read-only accessor --- .../README.md | 112 ++++++++++++++++++ .../benchmark/benchmark.js | 59 +++++++++ .../docs/repl.txt | 28 +++++ .../docs/types/index.d.ts | 63 ++++++++++ .../docs/types/test.ts | 57 +++++++++ .../examples/index.js | 41 +++++++ .../lib/index.js | 51 ++++++++ .../lib/main.js | 61 ++++++++++ .../package.json | 71 +++++++++++ .../test/test.js | 106 +++++++++++++++++ 10 files changed, 649 insertions(+) create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/README.md create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/examples/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/lib/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/lib/main.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/package.json create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/test/test.js diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/README.md b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/README.md new file mode 100644 index 000000000000..b721a91e06ef --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/README.md @@ -0,0 +1,112 @@ + + +# Configurable Read-Only Accessor + +> [Define][@stdlib/utils/define-property] a configurable **read-only** accessor. + +
+ +## Usage + + + +```javascript +var setConfigurableReadOnlyAccessor = require( '@stdlib/utils/define-configurable-read-only-accessor' ); +``` + +#### setConfigurableReadOnlyAccessor( obj, prop, getter ) + +[Defines][@stdlib/utils/define-property] a configurable **read-only** accessor. + + + + + +```javascript +function getter() { + return 'bar'; +} + +var obj = {}; + +setConfigurableReadOnlyAccessor( obj, 'foo', getter ); + +obj.foo = 'boop'; +// throws +``` + +
+ + + +
+ +## Notes + +- Configurable read-only accessors are **enumerable**. + +
+ + + +
+ +## Examples + + + + + +```javascript +var setConfigurableReadOnlyAccessor = require( '@stdlib/utils/define-configurable-read-only-accessor' ); + +function Foo( name ) { + if ( !(this instanceof Foo) ) { + return new Foo( name ); + } + setConfigurableReadOnlyAccessor( this, 'name', getName ); + return this; + + function getName() { + return name; + } +} + +var foo = new Foo( 'beep' ); + +try { + foo.name = 'boop'; +} catch ( err ) { + console.error( err.message ); +} +``` + +
+ + + +
+ +[@stdlib/utils/define-property]: https://github.com/stdlib-js/stdlib + +
+ + diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/benchmark/benchmark.js b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/benchmark/benchmark.js new file mode 100644 index 000000000000..30df00308db3 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/benchmark/benchmark.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var fromCodePoint = require( '@stdlib/string/from-code-point' ); +var pkg = require( './../package.json' ).name; +var setConfigurableReadOnlyAccessor = require( './../lib' ); // eslint-disable-line id-length + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var obj; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + obj = {}; + setConfigurableReadOnlyAccessor( obj, 'foo', getter( i ) ); + if ( !isString( obj.foo ) ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( obj.foo ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function getter( i ) { + var v = fromCodePoint( 97 + (i%26) ); + return get; + + function get() { + return v; + } + } +}); diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/repl.txt b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/repl.txt new file mode 100644 index 000000000000..9f64259e8fc5 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/repl.txt @@ -0,0 +1,28 @@ + +{{alias}}( obj, prop, getter ) + Defines a configurable read-only accessor. + + Configurable read-only accessors are enumerable. + + Parameters + ---------- + obj: Object + Object on which to define the property. + + prop: string|symbol + Property name. + + getter: Function + Get accessor. + + Examples + -------- + > var obj = {}; + > function getter() { return 'bar'; }; + > {{alias}}( obj, 'foo', getter ); + > obj.foo + 'bar' + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/index.d.ts b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/index.d.ts new file mode 100644 index 000000000000..2016d206ff74 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/index.d.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/// + +import { PropertyName } from '@stdlib/types/object'; + +/** +* Getter function. +* +* @returns property value +*/ +type Getter = () => any; + +/** +* Defines a configurable read-only accessor. +* +* ## Notes +* +* - Configurable read-only accessors are **enumerable**. +* +* @param obj - object on which to define property +* @param prop - property name +* @param getter - get accessor +* +* @example +* var obj = {}; +* +* function getter() { +* return 'bar'; +* } +* +* setConfigurableReadOnlyAccessor( obj, 'foo', getter ); +* +* try { +* obj.foo = 'boop'; +* } catch ( err ) { +* console.error( err.message ); +* } +*/ +declare function setConfigurableReadOnlyAccessor( obj: any, prop: PropertyName, getter: Getter ): void; // tslint:disable-line: max-line-length + + +// EXPORTS // + +export = setConfigurableReadOnlyAccessor; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/test.ts b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/test.ts new file mode 100644 index 000000000000..d0d11c2876fb --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/test.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import setConfigurableReadAccessor = require( './index' ); + + +// TESTS // + +// The function returns `undefined`... +{ + setConfigurableReadOnlyAccessor( {}, 'foo', (): string => 'bar' ); // $ExpectType void +} + +// The compiler throws an error if the function is provided a second argument which is not a valid property name... +{ + setConfigurableReadOnlyAccessor( {}, true, (): string => 'bar' ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, false, (): string => 'bar' ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, null, (): string => 'bar' ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, undefined, (): string => 'bar' ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, [], (): string => 'bar' ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, {}, (): string => 'bar' ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, ( x: number ): number => x, (): string => 'bar' ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a valid getter... +{ + setConfigurableReadOnlyAccessor( {}, 'foo', '5' ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, 'foo', 5 ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, 'foo', true ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, 'foo', false ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, 'foo', null ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, 'foo', undefined ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, 'foo', [] ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, 'foo', {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + setConfigurableReadOnlyAccessor(); // $ExpectError + setConfigurableReadOnlyAccessor( {} ); // $ExpectError + setConfigurableReadOnlyAccessor( {}, 'foo' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/examples/index.js b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/examples/index.js new file mode 100644 index 000000000000..59f908b68a4e --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var setConfigurableReadOnlyAccessor = require( './../lib' ); // eslint-disable-line id-length + +function Foo( name ) { + if ( !(this instanceof Foo) ) { + return new Foo( name ); + } + setConfigurableReadOnlyAccessor( this, 'name', getName ); + return this; + + function getName() { + return name; + } +} + +var foo = new Foo( 'beep' ); + +try { + foo.name = 'boop'; +} catch ( err ) { + console.error( err.message ); +} diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/lib/index.js b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/lib/index.js new file mode 100644 index 000000000000..eb82f57f24df --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/lib/index.js @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Define a configurable read-only accessor. +* +* @module @stdlib/utils/define-configurable-read-only-accessor +* +* @example +* var setConfigurableReadOnlyAccessor = require( '@stdlib/utils/define-configurable-read-only-accessor' ); +* +* function getter() { +* return 'bar'; +* } +* +* var obj = {}; +* +* setConfigurableReadOnlyAccessor( obj, 'foo', getter ); +* +* try { +* obj.foo = 'boop'; +* } catch ( err ) { +* console.error( err.message ); +* } +*/ + +// MODULES // + +var setConfigurableReadOnlyAccessor = require( './main.js' ); // eslint-disable-line id-length + + +// EXPORTS // + +module.exports = setConfigurableReadOnlyAccessor; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/lib/main.js b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/lib/main.js new file mode 100644 index 000000000000..5727e758f09f --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/lib/main.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var defineProperty = require( '@stdlib/utils/define-property' ); + + +// MAIN // + +/** +* Defines a configurable read-only accessor. +* +* @param {Object} obj - object on which to define the property +* @param {(string|symbol)} prop - property name +* @param {Function} getter - accessor +* +* @example +* function getter() { +* return 'bar'; +* } +* +* var obj = {}; +* +* setConfigurableReadOnlyAccessor( obj, 'foo', getter ); +* +* try { +* obj.foo = 'boop'; +* } catch ( err ) { +* console.error( err.message ); +* } +*/ +function setConfigurableReadOnlyAccessor( obj, prop, getter ) { // eslint-disable-line id-length + defineProperty( obj, prop, { + 'configurable': true, + 'enumerable': true, + 'get': getter + }); +} + + +// EXPORTS // + +module.exports = setConfigurableReadOnlyAccessor; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/package.json b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/package.json new file mode 100644 index 000000000000..5910208349fb --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/utils/define-configurable-read-only-accessor", + "version": "0.0.0", + "description": "Define a configurable read-only accessor.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdutils", + "stdutil", + "utilities", + "utility", + "utils", + "util", + "object", + "property", + "define", + "prop", + "read-only", + "writable", + "configurable", + "accessor", + "get", + "getter", + "enumerable" + ] +} diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/test/test.js b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/test/test.js new file mode 100644 index 000000000000..79e1fbe536e1 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/test/test.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var objectKeys = require( '@stdlib/utils/keys' ); +var defineProperty = require( '@stdlib/utils/define-property' ); +var propertyDescriptor = require( '@stdlib/utils/property-descriptor' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var setConfigurableReadOnlyAccessor = require( './../lib' ); // eslint-disable-line id-length + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.equal( typeof setConfigurableReadOnlyAccessor, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function sets a property on a provided object', function test( t ) { + var obj = {}; + setConfigurableReadOnlyAccessor( obj, 'foo', getter ); + t.equal( obj.foo, 'bar', 'returns expected value' ); + t.end(); + + function getter() { + return 'bar'; + } +}); + +tape( 'the read-only property is not writable', function test( t ) { + var obj = {}; + setConfigurableReadOnlyAccessor( obj, 'foo', getter ); + t.throws( foo, Error, 'property cannot be set' ); + t.end(); + + function getter() { + return 'bar'; + } + + function foo() { + obj.foo = 'bip'; + } +}); + +tape( 'the read-only property is configurable', function test( t ) { + var desc; + var obj; + + obj = {}; + setConfigurableReadOnlyAccessor( obj, 'foo', getter ); + setConfigurableReadOnlyAccessor( obj, 'beep', getter ); + + desc = { + 'configurable': true, + 'enumerable': false, + 'get': getter, + 'set': void 0 + }; + defineProperty( obj, 'foo', desc ); + t.deepEqual( propertyDescriptor( obj, 'foo' ), desc, 'property can be reconfigured' ); + + t.equal( obj.beep, 'bar', 'returns expected value' ); + t.equal( hasOwnProp( obj, 'beep' ), true, 'has property' ); + + // Configurable properties can be deleted... + delete obj.beep; + t.equal( obj.beep, void 0, 'returns expected value' ); + t.equal( hasOwnProp( obj, 'beep' ), false, 'does not have property' ); + + t.end(); + + function getter() { + return 'bar'; + } +}); + +tape( 'the read-only property is enumerable', function test( t ) { + var obj = {}; + setConfigurableReadOnlyAccessor( obj, 'foo', getter ); + t.deepEqual( objectKeys( obj ), [ 'foo' ], 'property is enumerable' ); + t.end(); + + function getter() { + return 'bar'; + } +}); From 4326f020281f9b4f3a83d50daa75b491c65c6ba4 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 15:25:39 -0700 Subject: [PATCH 076/142] Update namespace --- lib/node_modules/@stdlib/utils/lib/index.js | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/lib/node_modules/@stdlib/utils/lib/index.js b/lib/node_modules/@stdlib/utils/lib/index.js index d8e71ce7eab2..43fd1b1d507c 100644 --- a/lib/node_modules/@stdlib/utils/lib/index.js +++ b/lib/node_modules/@stdlib/utils/lib/index.js @@ -243,6 +243,15 @@ setReadOnly( utils, 'deepPluck', require( '@stdlib/utils/deep-pluck' ) ); */ setReadOnly( utils, 'deepSet', require( '@stdlib/utils/deep-set' ) ); +/** +* @name setConfigurableReadOnlyAccessor +* @memberof utils +* @readonly +* @type {Function} +* @see {@link module:@stdlib/utils/define-configurable-read-only-accessor} +*/ +setReadOnly( utils, 'setConfigurableReadOnlyAccessor', require( '@stdlib/utils/define-configurable-read-only-accessor' ) ); + /** * @name setConfigurableReadOnly * @memberof utils From 49cf77ab4393d9dcf671b094cd3852bba95c8401 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 15:26:15 -0700 Subject: [PATCH 077/142] Update namespace --- .../@stdlib/namespace/alias2pkg/data/data.csv | 1 + .../@stdlib/namespace/alias2pkg/data/data.json | 2 +- .../@stdlib/namespace/alias2related/data/data.csv | 3 ++- .../@stdlib/namespace/alias2related/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.txt | 1 + .../@stdlib/namespace/lib/namespace/s.js | 12 ++++++++++++ .../@stdlib/namespace/pkg2alias/data/data.csv | 1 + .../@stdlib/namespace/pkg2alias/data/data.json | 2 +- .../@stdlib/namespace/pkg2related/data/data.csv | 3 ++- .../@stdlib/namespace/pkg2related/data/data.json | 2 +- lib/node_modules/@stdlib/repl/code-blocks/lib/db.js | 1 + lib/node_modules/@stdlib/repl/help/lib/db.js | 3 ++- 13 files changed, 27 insertions(+), 8 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index dc96cb31280a..503f96655a86 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1760,6 +1760,7 @@ SECONDS_IN_WEEK,"@stdlib/constants/time/seconds-in-week" secondsInMonth,"@stdlib/time/seconds-in-month" secondsInYear,"@stdlib/time/seconds-in-year" setConfigurableReadOnly,"@stdlib/utils/define-configurable-read-only-property" +setConfigurableReadOnlyAccessor,"@stdlib/utils/define-configurable-read-only-accessor" setNonEnumerableProperty,"@stdlib/utils/define-nonenumerable-property" setNonEnumerableReadOnly,"@stdlib/utils/define-nonenumerable-read-only-property" setNonEnumerableReadOnlyAccessor,"@stdlib/utils/define-nonenumerable-read-only-accessor" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index 0a468e0857a0..5b7349a31faa 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ -{"AFINN_96":"@stdlib/datasets/afinn-96","AFINN_111":"@stdlib/datasets/afinn-111","alias2pkg":"@stdlib/namespace/alias2pkg","alias2related":"@stdlib/namespace/alias2related","aliases":"@stdlib/namespace/aliases","allocUnsafe":"@stdlib/buffer/alloc-unsafe","anova1":"@stdlib/stats/anova1","ANSCOMBES_QUARTET":"@stdlib/datasets/anscombes-quartet","any":"@stdlib/utils/any","anyBy":"@stdlib/utils/any-by","anyByAsync":"@stdlib/utils/async/any-by","anyByRight":"@stdlib/utils/any-by-right","anyByRightAsync":"@stdlib/utils/async/any-by-right","APERY":"@stdlib/constants/math/float64-apery","append":"@stdlib/utils/append","ARCH":"@stdlib/os/arch","argumentFunction":"@stdlib/utils/argument-function","ARGV":"@stdlib/process/argv","array":"@stdlib/ndarray/array","array2buffer":"@stdlib/buffer/from-array","array2iterator":"@stdlib/array/to-iterator","array2iteratorRight":"@stdlib/array/to-iterator-right","ArrayBuffer":"@stdlib/array/buffer","arraybuffer2buffer":"@stdlib/buffer/from-arraybuffer","arrayCtors":"@stdlib/array/ctors","arrayDataType":"@stdlib/array/dtype","arrayDataTypes":"@stdlib/array/dtypes","arrayMinDataType":"@stdlib/array/min-dtype","arrayNextDataType":"@stdlib/array/next-dtype","arrayPromotionRules":"@stdlib/array/promotion-rules","arraySafeCasts":"@stdlib/array/safe-casts","arraySameKindCasts":"@stdlib/array/same-kind-casts","arrayShape":"@stdlib/array/shape","arrayStream":"@stdlib/streams/node/from-array","arrayview2iterator":"@stdlib/array/to-view-iterator","arrayview2iteratorRight":"@stdlib/array/to-view-iterator-right","AsyncIteratorSymbol":"@stdlib/symbol/async-iterator","bartlettTest":"@stdlib/stats/bartlett-test","base.abs":"@stdlib/math/base/special/abs","base.abs2":"@stdlib/math/base/special/abs2","base.absdiff":"@stdlib/math/base/utils/absolute-difference","base.absInt32":"@stdlib/math/base/special/int32-abs","base.acos":"@stdlib/math/base/special/acos","base.acosh":"@stdlib/math/base/special/acosh","base.acoth":"@stdlib/math/base/special/acoth","base.acovercos":"@stdlib/math/base/special/acovercos","base.acoversin":"@stdlib/math/base/special/acoversin","base.ahavercos":"@stdlib/math/base/special/ahavercos","base.ahaversin":"@stdlib/math/base/special/ahaversin","base.asin":"@stdlib/math/base/special/asin","base.asinh":"@stdlib/math/base/special/asinh","base.atan":"@stdlib/math/base/special/atan","base.atan2":"@stdlib/math/base/special/atan2","base.atanh":"@stdlib/math/base/special/atanh","base.avercos":"@stdlib/math/base/special/avercos","base.aversin":"@stdlib/math/base/special/aversin","base.bernoulli":"@stdlib/math/base/special/bernoulli","base.besselj0":"@stdlib/math/base/special/besselj0","base.besselj1":"@stdlib/math/base/special/besselj1","base.bessely0":"@stdlib/math/base/special/bessely0","base.bessely1":"@stdlib/math/base/special/bessely1","base.beta":"@stdlib/math/base/special/beta","base.betainc":"@stdlib/math/base/special/betainc","base.betaincinv":"@stdlib/math/base/special/betaincinv","base.betaln":"@stdlib/math/base/special/betaln","base.binet":"@stdlib/math/base/special/binet","base.binomcoef":"@stdlib/math/base/special/binomcoef","base.binomcoefln":"@stdlib/math/base/special/binomcoefln","base.boxcox":"@stdlib/math/base/special/boxcox","base.boxcox1p":"@stdlib/math/base/special/boxcox1p","base.boxcox1pinv":"@stdlib/math/base/special/boxcox1pinv","base.boxcoxinv":"@stdlib/math/base/special/boxcoxinv","base.cabs":"@stdlib/math/base/complex/abs","base.cabs2":"@stdlib/math/base/complex/abs2","base.cadd":"@stdlib/math/base/complex/add","base.cbrt":"@stdlib/math/base/special/cbrt","base.cceil":"@stdlib/math/base/complex/ceil","base.cceiln":"@stdlib/math/base/complex/ceiln","base.ccis":"@stdlib/math/base/complex/cis","base.cdiv":"@stdlib/math/base/complex/divide","base.ceil":"@stdlib/math/base/special/ceil","base.ceil2":"@stdlib/math/base/special/ceil2","base.ceil10":"@stdlib/math/base/special/ceil10","base.ceilb":"@stdlib/math/base/special/ceilb","base.ceiln":"@stdlib/math/base/special/ceiln","base.ceilsd":"@stdlib/math/base/special/ceilsd","base.cexp":"@stdlib/math/base/complex/exp","base.cflipsign":"@stdlib/math/base/complex/flipsign","base.cfloor":"@stdlib/math/base/complex/floor","base.cfloorn":"@stdlib/math/base/complex/floorn","base.cinv":"@stdlib/math/base/complex/inv","base.clamp":"@stdlib/math/base/special/clamp","base.cmul":"@stdlib/math/base/complex/multiply","base.cneg":"@stdlib/math/base/complex/negate","base.continuedFraction":"@stdlib/math/base/tools/continued-fraction","base.copysign":"@stdlib/math/base/special/copysign","base.cos":"@stdlib/math/base/special/cos","base.cosh":"@stdlib/math/base/special/cosh","base.cosm1":"@stdlib/math/base/special/cosm1","base.cospi":"@stdlib/math/base/special/cospi","base.covercos":"@stdlib/math/base/special/covercos","base.coversin":"@stdlib/math/base/special/coversin","base.cphase":"@stdlib/math/base/complex/phase","base.cpolar":"@stdlib/math/base/complex/polar","base.cround":"@stdlib/math/base/complex/round","base.croundn":"@stdli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SQRT_THREE":"@stdlib/constants/math/float64-sqrt-three","SQRT_TWO":"@stdlib/constants/math/float64-sqrt-two","SQRT_TWO_PI":"@stdlib/constants/math/float64-sqrt-two-pi","Stack":"@stdlib/utils/stack","startcase":"@stdlib/string/startcase","startsWith":"@stdlib/string/starts-with","STOPWORDS_EN":"@stdlib/datasets/stopwords-en","stridedarray2iterator":"@stdlib/array/to-strided-iterator","stridedArrayStream":"@stdlib/streams/node/from-strided-array","string2buffer":"@stdlib/buffer/from-string","sub2ind":"@stdlib/ndarray/sub2ind","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-multi-hop-sensor-network","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-single-hop-sensor-network","Symbol":"@stdlib/symbol/ctor","tabulate":"@stdlib/utils/tabulate","tabulateBy":"@stdlib/utils/tabulate-by","tabulateByAsync":"@stdlib/utils/async/tabulate-by","tic":"@stdlib/time/tic","timeit":"@stdlib/utils/timeit","tmpdir":"@stdlib/os/tmpdir","toc":"@stdlib/time/toc","tokenize":"@stdlib/nlp/tokenize","transformStream":"@stdlib/streams/node/transform","trim":"@stdlib/string/trim","trycatch":"@stdlib/utils/try-catch","trycatchAsync":"@stdlib/utils/async/try-catch","tryFunction":"@stdlib/utils/try-function","tryRequire":"@stdlib/utils/try-require","trythen":"@stdlib/utils/try-then","trythenAsync":"@stdlib/utils/async/try-then","ttest":"@stdlib/stats/ttest","ttest2":"@stdlib/stats/ttest2","TWO_PI":"@stdlib/constants/math/float64-two-pi","typedarray":"@stdlib/array/typed","typedarray2json":"@stdlib/array/to-json","typedarrayComplexCtors":"@stdlib/array/typed-complex-ctors","typedarrayComplexDataTypes":"@stdlib/array/typed-complex-dtypes","typedarrayCtors":"@stdlib/array/typed-ctors","typedarrayDataTypes":"@stdlib/array/typed-dtypes","typedarraypool":"@stdlib/array/pool","typemax":"@stdlib/utils/type-max","typemin":"@stdlib/utils/type-min","typeOf":"@stdlib/utils/type-of","UINT8_MAX":"@stdlib/constants/math/uint8-max","UINT8_NUM_BYTES":"@stdlib/constants/math/uint8-num-bytes","Uint8Array":"@stdlib/array/uint8","Uint8ClampedArray":"@stdlib/array/uint8c","UINT16_MAX":"@stdlib/constants/math/uint16-max","UINT16_NUM_BYTES":"@stdlib/constants/math/uint16-num-bytes","Uint16Array":"@stdlib/array/uint16","UINT32_MAX":"@stdlib/constants/math/uint32-max","UINT32_NUM_BYTES":"@stdlib/constants/math/uint32-num-bytes","Uint32Array":"@stdlib/array/uint32","umask":"@stdlib/process/umask","uncapitalize":"@stdlib/string/uncapitalize","uncapitalizeKeys":"@stdlib/utils/uncapitalize-keys","uncurry":"@stdlib/utils/uncurry","uncurryRight":"@stdlib/utils/uncurry-right","UNICODE_MAX":"@stdlib/constants/string/unicode-max","UNICODE_MAX_BMP":"@stdlib/constants/string/unicode-max-bmp","UnicodeColumnChartSparkline":"@stdlib/plot/sparklines/unicode/column","UnicodeLineChartSparkline":"@stdlib/plot/sparklines/unicode/line","UnicodeSparkline":"@stdlib/plot/sparklines/unicode","UnicodeTristateChartSparkline":"@stdlib/plot/sparklines/unicode/tristate","UnicodeUpDownChartSparkline":"@stdlib/plot/sparklines/unicode/up-down","UnicodeWinLossChartSparkline":"@stdlib/plot/sparklines/unicode/win-loss","unlink":"@stdlib/fs/unlink","unshift":"@stdlib/utils/unshift","until":"@stdlib/utils/until","untilAsync":"@stdlib/utils/async/until","untilEach":"@stdlib/utils/until-each","untilEachRight":"@stdlib/utils/until-each-right","unzip":"@stdlib/utils/unzip","uppercase":"@stdlib/string/uppercase","uppercaseKeys":"@stdlib/utils/uppercase-keys","US_STATES_ABBR":"@stdlib/datasets/us-states-abbr","US_STATES_CAPITALS":"@stdlib/datasets/us-states-capitals","US_STATES_CAPITALS_NAMES":"@stdlib/datasets/us-states-capitals-names","US_STATES_NAMES":"@stdlib/datasets/us-states-names","US_STATES_NAMES_CAPITALS":"@stdlib/datasets/us-states-names-capitals","utf16ToUTF8Array":"@stdlib/string/utf16-to-utf8-array","vartest":"@stdlib/stats/vartest","waterfall":"@stdlib/utils/async/series-waterfall","whileAsync":"@stdlib/utils/async/while","whileEach":"@stdlib/utils/while-each","whileEachRight":"@stdlib/utils/while-each-right","whilst":"@stdlib/utils/while","writableProperties":"@stdlib/utils/writable-properties","writablePropertiesIn":"@stdlib/utils/writable-properties-in","writablePropertyNames":"@stdlib/utils/writable-property-names","writablePropertyNamesIn":"@stdlib/utils/writable-property-names-in","writablePropertySymbols":"@stdlib/utils/writable-property-symbols","writablePropertySymbolsIn":"@stdlib/utils/writable-property-symbols-in","writeFile":"@stdlib/fs/write-file","zip":"@stdlib/utils/zip","ztest":"@stdlib/stats/ztest","ztest2":"@stdlib/stats/ztest2"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv index 930537bda3a1..48ddfda47742 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv @@ -1759,7 +1759,8 @@ SECONDS_IN_MINUTE,"" SECONDS_IN_WEEK,"" secondsInMonth,"secondsInYear" secondsInYear,"secondsInMonth" -setConfigurableReadOnly,"defineProperty,setReadOnly" +setConfigurableReadOnly,"setConfigurableReadOnlyAccessor,defineProperty,setReadOnly" +setConfigurableReadOnlyAccessor,"setConfigurableReadOnly,defineProperty,setReadOnlyAccessor" setNonEnumerableProperty,"setNonEnumerableReadOnlyAccessor,setNonEnumerableReadOnly,setNonEnumerableReadWriteAccessor,setNonEnumerableWriteOnlyAccessor,setReadOnly" setNonEnumerableReadOnly,"setNonEnumerableProperty,setNonEnumerableReadOnlyAccessor,setNonEnumerableReadWriteAccessor,setNonEnumerableWriteOnlyAccessor,setReadOnly" setNonEnumerableReadOnlyAccessor,"setNonEnumerableProperty,setNonEnumerableReadOnly,setNonEnumerableReadWriteAccessor,setNonEnumerableWriteOnlyAccessor,setReadOnlyAccessor" diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.json b/lib/node_modules/@stdlib/namespace/alias2related/data/data.json index 3ef802570777..2a942972d481 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index c57728e08332..f0bd11aa5655 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1760,6 +1760,7 @@ SECONDS_IN_WEEK secondsInMonth secondsInYear setConfigurableReadOnly +setConfigurableReadOnlyAccessor setNonEnumerableProperty setNonEnumerableReadOnly setNonEnumerableReadOnlyAccessor diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/s.js b/lib/node_modules/@stdlib/namespace/lib/namespace/s.js index f8195385d2b7..2b8c3167ba7e 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/s.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/s.js @@ -178,6 +178,18 @@ ns.push({ ] }); +ns.push({ + 'alias': 'setConfigurableReadOnlyAccessor', + 'path': '@stdlib/utils/define-configurable-read-only-accessor', + 'value': require( '@stdlib/utils/define-configurable-read-only-accessor' ), + 'type': 'Function', + 'related': [ + '@stdlib/utils/define-configurable-read-only-property', + '@stdlib/utils/define-property', + '@stdlib/utils/define-read-only-accessor' + ] +}); + ns.push({ 'alias': 'setNonEnumerableProperty', 'path': '@stdlib/utils/define-nonenumerable-property', diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index edb1806bec3c..173476f568b6 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -1760,6 +1760,7 @@ "@stdlib/time/seconds-in-month",secondsInMonth "@stdlib/time/seconds-in-year",secondsInYear "@stdlib/utils/define-configurable-read-only-property",setConfigurableReadOnly +"@stdlib/utils/define-configurable-read-only-accessor",setConfigurableReadOnlyAccessor "@stdlib/utils/define-nonenumerable-property",setNonEnumerableProperty "@stdlib/utils/define-nonenumerable-read-only-property",setNonEnumerableReadOnly "@stdlib/utils/define-nonenumerable-read-only-accessor",setNonEnumerableReadOnlyAccessor diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index 22e754e9230c..072251860706 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ 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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv index cc3bd6f30355..6b4d1790476d 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv @@ -1759,7 +1759,8 @@ "@stdlib/constants/time/seconds-in-week","" "@stdlib/time/seconds-in-month","@stdlib/time/seconds-in-year" "@stdlib/time/seconds-in-year","@stdlib/time/seconds-in-month" -"@stdlib/utils/define-configurable-read-only-property","@stdlib/utils/define-property,@stdlib/utils/define-read-only-property" +"@stdlib/utils/define-configurable-read-only-property","@stdlib/utils/define-configurable-read-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-read-only-property" +"@stdlib/utils/define-configurable-read-only-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-property,@stdlib/utils/define-read-only-accessor" "@stdlib/utils/define-nonenumerable-property","@stdlib/utils/define-nonenumerable-read-only-accessor,@stdlib/utils/define-nonenumerable-read-only-property,@stdlib/utils/define-nonenumerable-read-write-accessor,@stdlib/utils/define-nonenumerable-write-only-accessor,@stdlib/utils/define-read-only-property" "@stdlib/utils/define-nonenumerable-read-only-property","@stdlib/utils/define-nonenumerable-property,@stdlib/utils/define-nonenumerable-read-only-accessor,@stdlib/utils/define-nonenumerable-read-write-accessor,@stdlib/utils/define-nonenumerable-write-only-accessor,@stdlib/utils/define-read-only-property" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index 446469f35c84..46ebb0fc946c 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -1777,6 +1777,7 @@ var db = { "secondsInMonth": "num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n", "secondsInYear": "num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n", "setConfigurableReadOnly": "obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", + "setConfigurableReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", "setNonEnumerableProperty": "obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n", "setNonEnumerableReadOnly": "obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", "setNonEnumerableReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index aa30bd2bd9d3..9f2bfe8f4bf0 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -1777,7 +1777,8 @@ var db = { "SECONDS_IN_WEEK": "\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n", "secondsInMonth": "\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n", "secondsInYear": "\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n", - "setConfigurableReadOnly": "\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperty, setReadOnly\n", + "setConfigurableReadOnly": "\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, defineProperty, setReadOnly\n", + "setConfigurableReadOnlyAccessor": "\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, defineProperty, setReadOnlyAccessor\n", "setNonEnumerableProperty": "\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", "setNonEnumerableReadOnly": "\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", "setNonEnumerableReadOnlyAccessor": "\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n", From 1e96dd7c656f359632e3c26f2b26a3925d2439ae Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 17:18:16 -0700 Subject: [PATCH 078/142] Fix variable name --- .../define-configurable-read-only-accessor/docs/types/test.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/test.ts b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/test.ts index d0d11c2876fb..45090def22eb 100644 --- a/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/test.ts +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-only-accessor/docs/types/test.ts @@ -16,7 +16,7 @@ * limitations under the License. */ -import setConfigurableReadAccessor = require( './index' ); +import setConfigurableReadOnlyAccessor = require( './index' ); // TESTS // From b4494b2a3a5bf288a99e320dec737ae47474e4e9 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 17:43:00 -0700 Subject: [PATCH 079/142] Add utility to define a configurable write-only accessor --- .../README.md | 109 ++++++++++++++++ .../benchmark/benchmark.js | 54 ++++++++ .../docs/repl.txt | 30 +++++ .../docs/types/index.d.ts | 60 +++++++++ .../docs/types/test.ts | 57 +++++++++ .../examples/index.js | 37 ++++++ .../lib/index.js | 48 +++++++ .../lib/main.js | 58 +++++++++ .../package.json | 71 +++++++++++ .../test/test.js | 117 ++++++++++++++++++ 10 files changed, 641 insertions(+) create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/README.md create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/examples/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/main.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/package.json create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/test/test.js diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/README.md b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/README.md new file mode 100644 index 000000000000..e27b53c81915 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/README.md @@ -0,0 +1,109 @@ + + +# Configurable Write-Only Accessor + +> [Define][@stdlib/utils/define-property] a configurable **write-only** accessor. + +
+ +## Usage + + + +```javascript +var setConfigurableWriteOnlyAccessor = require( '@stdlib/utils/define-configurable-write-only-accessor' ); +``` + +#### setConfigurableWriteOnlyAccessor( obj, prop, setter ) + +[Defines][@stdlib/utils/define-property] a configurable **write-only** accessor. + + + +```javascript +var obj = {}; +var val = ''; + +function setter( v ) { + val = v; +} + +setConfigurableWriteOnlyAccessor( obj, 'foo', setter ); + +obj.foo = 'boop'; + +var bool = ( val === 'boop' ); +// returns true +``` + +
+ + + +
+ +## Notes + +- Configurable write-only accessors are **enumerable**. + +
+ + + +
+ +## Examples + + + + + +```javascript +var setConfigurableWriteOnlyAccessor = require( '@stdlib/utils/define-configurable-write-only-accessor' ); + +function Foo( secret ) { + if ( !(this instanceof Foo) ) { + return new Foo( secret ); + } + setConfigurableWriteOnlyAccessor( this, 'secret', setter ); + return this; + + function setter( v ) { + secret = v; + } +} + +var foo = new Foo( 'beep' ); + +foo.secret = 'boop'; +``` + +
+ + + +
+ +[@stdlib/utils/define-property]: https://github.com/stdlib-js/stdlib + +
+ + diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/benchmark/benchmark.js b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/benchmark/benchmark.js new file mode 100644 index 000000000000..87fc32ba0c58 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/benchmark/benchmark.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pkg = require( './../package.json' ).name; +var setConfigurableWriteOnlyAccessor = require( './../lib' ); // eslint-disable-line id-length + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var obj; + var val; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + obj = {}; + setConfigurableWriteOnlyAccessor( obj, 'foo', setter ); + obj.foo = i; + if ( val !== i ) { + b.fail( 'unexpected result' ); + } + } + b.toc(); + if ( val !== (i-1) ) { + b.fail( 'unexpected result' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function setter( v ) { + val = v; + } +}); diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/repl.txt b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/repl.txt new file mode 100644 index 000000000000..3e2fb7fae9c6 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/repl.txt @@ -0,0 +1,30 @@ + +{{alias}}( obj, prop, setter ) + Defines a configurable write-only accessor. + + Configurable write-only accessors are enumerable. + + Parameters + ---------- + obj: Object + Object on which to define the property. + + prop: string|symbol + Property name. + + setter: Function + Set accessor. + + Examples + -------- + > var obj = {}; + > var val = ''; + > function setter( v ) { val = v; }; + > {{alias}}( obj, 'foo', setter ); + > obj.foo = 'bar'; + > val + 'bar' + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/types/index.d.ts b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/types/index.d.ts new file mode 100644 index 000000000000..e18826b35f41 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/types/index.d.ts @@ -0,0 +1,60 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/// + +import { PropertyName } from '@stdlib/types/object'; + +/** +* Setter function. +* +* @param value - property value +*/ +type Setter = ( x: any ) => void; + +/** +* Defines a configurable write-only accessor. +* +* ## Notes +* +* - Configurable write-only accessors are **enumerable**. +* +* @param obj - object on which to define property +* @param prop - property name +* @param setter - set accessor +* +* @example +* var obj = {}; +* var val = ''; +* +* function setter( v ) { +* val = v; +* } +* +* setConfigurableWriteOnlyAccessor( obj, 'foo', setter ); +* +* obj.foo = 'beep'; +*/ +declare function setConfigurableWriteOnlyAccessor( obj: any, prop: PropertyName, setter: Setter ): void; // tslint:disable-line: max-line-length + + +// EXPORTS // + +export = setConfigurableWriteOnlyAccessor; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/types/test.ts b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/types/test.ts new file mode 100644 index 000000000000..e90e911ab6b0 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/docs/types/test.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import setConfigurableWriteOnlyAccessor = require( './index' ); + + +// TESTS // + +// The function returns `undefined`... +{ + setConfigurableWriteOnlyAccessor( {}, 'foo', ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectType void +} + +// The compiler throws an error if the function is provided a second argument which is not a valid property name... +{ + setConfigurableWriteOnlyAccessor( {}, true, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, false, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, null, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, undefined, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, [], ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, {}, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, ( x: number ): number => x, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a valid setter... +{ + setConfigurableWriteOnlyAccessor( {}, 'foo', '5' ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, 'foo', 5 ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, 'foo', true ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, 'foo', false ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, 'foo', null ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, 'foo', undefined ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, 'foo', [] ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, 'foo', {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + setConfigurableWriteOnlyAccessor(); // $ExpectError + setConfigurableWriteOnlyAccessor( {} ); // $ExpectError + setConfigurableWriteOnlyAccessor( {}, 'foo' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/examples/index.js b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/examples/index.js new file mode 100644 index 000000000000..82355b5ef8fa --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var setConfigurableWriteOnlyAccessor = require( './../lib' ); // eslint-disable-line id-length + +function Foo( secret ) { + if ( !(this instanceof Foo) ) { + return new Foo( secret ); + } + setConfigurableWriteOnlyAccessor( this, 'secret', setter ); + return this; + + function setter( v ) { + secret = v; + } +} + +var foo = new Foo( 'beep' ); + +foo.secret = 'boop'; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/index.js b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/index.js new file mode 100644 index 000000000000..8a369f050326 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/index.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Define a configurable write-only accessor. +* +* @module @stdlib/utils/define-configurable-write-only-accessor +* +* @example +* var setConfigurableWriteOnlyAccessor = require( '@stdlib/utils/define-configurable-write-only-accessor' ); +* +* var obj = {}; +* var val = ''; +* +* function setter( v ) { +* val = v; +* } +* +* setConfigurableWriteOnlyAccessor( obj, 'foo', setter ); +* +* obj.foo = 'beep'; +*/ + +// MODULES // + +var setConfigurableWriteOnlyAccessor = require( './main.js' ); // eslint-disable-line id-length + + +// EXPORTS // + +module.exports = setConfigurableWriteOnlyAccessor; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/main.js b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/main.js new file mode 100644 index 000000000000..0becf92cadd7 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/main.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var defineProperty = require( '@stdlib/utils/define-property' ); + + +// MAIN // + +/** +* Defines a configurable write-only accessor. +* +* @param {Object} obj - object on which to define the property +* @param {(string|symbol)} prop - property name +* @param {Function} setter - accessor +* +* @example +* var obj = {}; +* var val = ''; +* +* function setter( v ) { +* val = v; +* } +* +* setConfigurableWriteOnlyAccessor( obj, 'foo', setter ); +* +* obj.foo = 'beep'; +*/ +function setConfigurableWriteOnlyAccessor( obj, prop, setter ) { // eslint-disable-line id-length + defineProperty( obj, prop, { + 'configurable': true, + 'enumerable': false, + 'set': setter + }); +} + + +// EXPORTS // + +module.exports = setConfigurableWriteOnlyAccessor; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/package.json b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/package.json new file mode 100644 index 000000000000..5d596a25c6fb --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/utils/define-configurable-write-only-accessor", + "version": "0.0.0", + "description": "Define a configurable write-only accessor.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdutils", + "stdutil", + "utilities", + "utility", + "utils", + "util", + "object", + "property", + "define", + "prop", + "write-only", + "writable", + "configurable", + "accessor", + "set", + "setter", + "enumerable" + ] +} diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/test/test.js b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/test/test.js new file mode 100644 index 000000000000..5ce00c536729 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/test/test.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var objectKeys = require( '@stdlib/utils/keys' ); +var defineProperty = require( '@stdlib/utils/define-property' ); +var propertyDescriptor = require( '@stdlib/utils/property-descriptor' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var setConfigurableWriteOnlyAccessor = require( './../lib' ); // eslint-disable-line id-length + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.equal( typeof setConfigurableWriteOnlyAccessor, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function sets a property on a provided object', function test( t ) { + var obj = {}; + var val = ''; + + setConfigurableWriteOnlyAccessor( obj, 'foo', setter ); + obj.foo = 'bar'; + + t.equal( val, 'bar', 'equals expected value' ); + t.end(); + + function setter( v ) { + val = v; + } +}); + +tape( 'the write-only property is not readable', function test( t ) { + var obj = {}; + var val = ''; + + setConfigurableWriteOnlyAccessor( obj, 'foo', setter ); + t.equal( obj.foo, void 0, 'property cannot be get' ); + + t.equal( val, '', 'equals expected value' ); + t.end(); + + function setter(v ) { + val = v; + } +}); + +tape( 'the write-only property is not configurable', function test( t ) { + var desc; + var obj; + var val; + + val = ''; + + obj = {}; + setConfigurableWriteOnlyAccessor( obj, 'foo', setter ); + setConfigurableWriteOnlyAccessor( obj, 'beep', setter ); + + desc = { + 'configurable': true, + 'enumerable': false, + 'set': setter, + 'get': void 0 + }; + defineProperty( obj, 'foo', desc ); + t.deepEqual( propertyDescriptor( obj, 'foo' ), desc, 'property can be reconfigured' ); + + t.equal( hasOwnProp( obj, 'beep' ), true, 'has property' ); + + // Configurable properties can be deleted... + delete obj.beep; + t.equal( obj.beep, void 0, 'returns expected value' ); + t.equal( hasOwnProp( obj, 'beep' ), false, 'does not have property' ); + + t.equal( val, '', 'equals expected value' ); + t.end(); + + function setter( v ) { + val = v; + } +}); + +tape( 'the write-only property is enumerable', function test( t ) { + var obj = {}; + var val = ''; + + setConfigurableWriteOnlyAccessor( obj, 'foo', setter ); + t.deepEqual( objectKeys( obj ), [ 'foo' ], 'property is enumerable' ); + + t.equal( val, '', 'equals expected value' ); + t.end(); + + function setter( v ) { + val = v; + } +}); From 20f5f4e7f5ced66ae2281daf006362533e366fba Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 17:44:51 -0700 Subject: [PATCH 080/142] Update namespace --- lib/node_modules/@stdlib/utils/lib/index.js | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/lib/node_modules/@stdlib/utils/lib/index.js b/lib/node_modules/@stdlib/utils/lib/index.js index 43fd1b1d507c..64a3e0895303 100644 --- a/lib/node_modules/@stdlib/utils/lib/index.js +++ b/lib/node_modules/@stdlib/utils/lib/index.js @@ -261,6 +261,15 @@ setReadOnly( utils, 'setConfigurableReadOnlyAccessor', require( '@stdlib/utils/d */ setReadOnly( utils, 'setConfigurableReadOnly', require( '@stdlib/utils/define-configurable-read-only-property' ) ); +/** +* @name setConfigurableWriteOnlyAccessor +* @memberof utils +* @readonly +* @type {Function} +* @see {@link module:@stdlib/utils/define-configurable-write-only-accessor} +*/ +setReadOnly( utils, 'setConfigurableWriteOnlyAccessor', require( '@stdlib/utils/define-configurable-write-only-accessor' ) ); + /** * @name setNonEnumerableProperty * @memberof utils From d5078db5b620a2c8e70c6a227ee1d1a4c3341171 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 17:51:19 -0700 Subject: [PATCH 081/142] Update namespace --- .../@stdlib/namespace/alias2pkg/data/data.csv | 1 + .../@stdlib/namespace/alias2pkg/data/data.json | 2 +- .../namespace/alias2related/data/data.csv | 3 ++- .../namespace/alias2related/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.txt | 1 + .../@stdlib/namespace/lib/namespace/s.js | 17 +++++++++++++++++ .../@stdlib/namespace/pkg2alias/data/data.csv | 1 + .../@stdlib/namespace/pkg2alias/data/data.json | 2 +- .../@stdlib/namespace/pkg2related/data/data.csv | 3 ++- .../namespace/pkg2related/data/data.json | 2 +- .../@stdlib/repl/code-blocks/lib/db.js | 1 + lib/node_modules/@stdlib/repl/help/lib/db.js | 3 ++- 13 files changed, 32 insertions(+), 8 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index 503f96655a86..7aecabbf1ca2 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1761,6 +1761,7 @@ secondsInMonth,"@stdlib/time/seconds-in-month" secondsInYear,"@stdlib/time/seconds-in-year" setConfigurableReadOnly,"@stdlib/utils/define-configurable-read-only-property" setConfigurableReadOnlyAccessor,"@stdlib/utils/define-configurable-read-only-accessor" +setConfigurableWriteOnlyAccessor,"@stdlib/utils/define-configurable-write-only-accessor" setNonEnumerableProperty,"@stdlib/utils/define-nonenumerable-property" setNonEnumerableReadOnly,"@stdlib/utils/define-nonenumerable-read-only-property" setNonEnumerableReadOnlyAccessor,"@stdlib/utils/define-nonenumerable-read-only-accessor" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index 5b7349a31faa..cb5c1e3f8077 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ 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araswamy/variance","base.dists.laplace.cdf":"@stdlib/stats/base/dists/laplace/cdf","base.dists.laplace.entropy":"@stdlib/stats/base/dists/laplace/entropy","base.dists.laplace.kurtosis":"@stdlib/stats/base/dists/laplace/kurtosis","base.dists.laplace.Laplace":"@stdlib/stats/base/dists/laplace/ctor","base.dists.laplace.logcdf":"@stdlib/stats/base/dists/laplace/logcdf","base.dists.laplace.logpdf":"@stdlib/stats/base/dists/laplace/logpdf","base.dists.laplace.mean":"@stdlib/stats/base/dists/laplace/mean","base.dists.laplace.median":"@stdlib/stats/base/dists/laplace/median","base.dists.laplace.mgf":"@stdlib/stats/base/dists/laplace/mgf","base.dists.laplace.mode":"@stdlib/stats/base/dists/laplace/mode","base.dists.laplace.pdf":"@stdlib/stats/base/dists/laplace/pdf","base.dists.laplace.quantile":"@stdlib/stats/base/dists/laplace/quantile","base.dists.laplace.skewness":"@stdlib/stats/base/dists/laplace/skewness","base.dists.laplace.stdev":"@stdlib/stats/base/dists/laplace/stdev","base.dists.laplace.variance":"@stdlib/stats/base/dists/laplace/variance","base.dists.levy.cdf":"@stdlib/stats/base/dists/levy/cdf","base.dists.levy.entropy":"@stdlib/stats/base/dists/levy/entropy","base.dists.levy.Levy":"@stdlib/stats/base/dists/levy/ctor","base.dists.levy.logcdf":"@stdlib/stats/base/dists/levy/logcdf","base.dists.levy.logpdf":"@stdlib/stats/base/dists/levy/logpdf","base.dists.levy.mean":"@stdlib/stats/base/dists/levy/mean","base.dists.levy.median":"@stdlib/stats/base/dists/levy/median","base.dists.levy.mode":"@stdlib/stats/base/dists/levy/mode","base.dists.levy.pdf":"@stdlib/stats/base/dists/levy/pdf","base.dists.levy.quantile":"@stdlib/stats/base/dists/levy/quantile","base.dists.levy.stdev":"@stdlib/stats/base/dists/levy/stdev","base.dists.levy.variance":"@stdlib/stats/base/dists/levy/variance","base.dists.logistic.cdf":"@stdlib/stats/base/dists/logistic/cdf","base.dists.logistic.entropy":"@stdlib/stats/base/dists/logistic/entropy","base.dists.logistic.kurtosis":"@stdlib/stats/base/dists/logistic/kurtosis","base.dists.logistic.logcdf":"@stdlib/stats/base/dists/logistic/logcdf","base.dists.logistic.Logistic":"@stdlib/stats/base/dists/logistic/ctor","base.dists.logistic.logpdf":"@stdlib/stats/base/dists/logistic/logpdf","base.dists.logistic.mean":"@stdlib/stats/base/dists/logistic/mean","base.dists.logistic.median":"@stdlib/stats/base/dists/logistic/median","base.dists.logistic.mgf":"@stdlib/stats/base/dists/logistic/mgf","base.dists.logistic.mode":"@stdlib/stats/base/dists/logistic/mode","base.dists.logistic.pdf":"@stdlib/stats/base/dists/logistic/pdf","base.dists.logistic.quantile":"@stdlib/stats/base/dists/logistic/quantile","base.dists.logistic.skewness":"@stdlib/stats/base/dists/logistic/skewness","base.dists.logistic.stdev":"@stdlib/stats/base/dists/logistic/stdev","base.dists.logistic.variance":"@stdlib/stats/base/dists/logistic/variance","base.dists.lognormal.cdf":"@stdlib/stats/base/dists/lognormal/cdf","base.dists.lognormal.entropy":"@stdlib/stats/base/dists/lognormal/entropy","base.dists.lognormal.kurtosis":"@stdlib/stats/base/dists/lognormal/kurtosis","base.dists.lognormal.LogNormal":"@stdlib/stats/base/dists/lognormal/ctor","base.dists.lognormal.logpdf":"@stdlib/stats/base/dists/lognormal/logpdf","base.dists.lognormal.mean":"@stdlib/stats/base/dists/lognormal/mean","base.dists.lognormal.median":"@stdlib/stats/base/dists/lognormal/median","base.dists.lognormal.mode":"@stdlib/stats/base/dists/lognormal/mode","base.dists.lognormal.pdf":"@stdlib/stats/base/dists/lognormal/pdf","base.dists.lognormal.quantile":"@stdlib/stats/base/dists/lognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdli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araswamy/variance","base.dists.laplace.cdf":"@stdlib/stats/base/dists/laplace/cdf","base.dists.laplace.entropy":"@stdlib/stats/base/dists/laplace/entropy","base.dists.laplace.kurtosis":"@stdlib/stats/base/dists/laplace/kurtosis","base.dists.laplace.Laplace":"@stdlib/stats/base/dists/laplace/ctor","base.dists.laplace.logcdf":"@stdlib/stats/base/dists/laplace/logcdf","base.dists.laplace.logpdf":"@stdlib/stats/base/dists/laplace/logpdf","base.dists.laplace.mean":"@stdlib/stats/base/dists/laplace/mean","base.dists.laplace.median":"@stdlib/stats/base/dists/laplace/median","base.dists.laplace.mgf":"@stdlib/stats/base/dists/laplace/mgf","base.dists.laplace.mode":"@stdlib/stats/base/dists/laplace/mode","base.dists.laplace.pdf":"@stdlib/stats/base/dists/laplace/pdf","base.dists.laplace.quantile":"@stdlib/stats/base/dists/laplace/quantile","base.dists.laplace.skewness":"@stdlib/stats/base/dists/laplace/skewness","base.dists.laplace.stdev":"@stdlib/stats/base/dists/laplace/stdev","base.dists.laplace.variance":"@stdlib/stats/base/dists/laplace/variance","base.dists.levy.cdf":"@stdlib/stats/base/dists/levy/cdf","base.dists.levy.entropy":"@stdlib/stats/base/dists/levy/entropy","base.dists.levy.Levy":"@stdlib/stats/base/dists/levy/ctor","base.dists.levy.logcdf":"@stdlib/stats/base/dists/levy/logcdf","base.dists.levy.logpdf":"@stdlib/stats/base/dists/levy/logpdf","base.dists.levy.mean":"@stdlib/stats/base/dists/levy/mean","base.dists.levy.median":"@stdlib/stats/base/dists/levy/median","base.dists.levy.mode":"@stdlib/stats/base/dists/levy/mode","base.dists.levy.pdf":"@stdlib/stats/base/dists/levy/pdf","base.dists.levy.quantile":"@stdlib/stats/base/dists/levy/quantile","base.dists.levy.stdev":"@stdlib/stats/base/dists/levy/stdev","base.dists.levy.variance":"@stdlib/stats/base/dists/levy/variance","base.dists.logistic.cdf":"@stdlib/stats/base/dists/logistic/cdf","base.dists.logistic.entropy":"@stdlib/stats/base/dists/logistic/entropy","base.dists.logistic.kurtosis":"@stdlib/stats/base/dists/logistic/kurtosis","base.dists.logistic.logcdf":"@stdlib/stats/base/dists/logistic/logcdf","base.dists.logistic.Logistic":"@stdlib/stats/base/dists/logistic/ctor","base.dists.logistic.logpdf":"@stdlib/stats/base/dists/logistic/logpdf","base.dists.logistic.mean":"@stdlib/stats/base/dists/logistic/mean","base.dists.logistic.median":"@stdlib/stats/base/dists/logistic/median","base.dists.logistic.mgf":"@stdlib/stats/base/dists/logistic/mgf","base.dists.logistic.mode":"@stdlib/stats/base/dists/logistic/mode","base.dists.logistic.pdf":"@stdlib/stats/base/dists/logistic/pdf","base.dists.logistic.quantile":"@stdlib/stats/base/dists/logistic/quantile","base.dists.logistic.skewness":"@stdlib/stats/base/dists/logistic/skewness","base.dists.logistic.stdev":"@stdlib/stats/base/dists/logistic/stdev","base.dists.logistic.variance":"@stdlib/stats/base/dists/logistic/variance","base.dists.lognormal.cdf":"@stdlib/stats/base/dists/lognormal/cdf","base.dists.lognormal.entropy":"@stdlib/stats/base/dists/lognormal/entropy","base.dists.lognormal.kurtosis":"@stdlib/stats/base/dists/lognormal/kurtosis","base.dists.lognormal.LogNormal":"@stdlib/stats/base/dists/lognormal/ctor","base.dists.lognormal.logpdf":"@stdlib/stats/base/dists/lognormal/logpdf","base.dists.lognormal.mean":"@stdlib/stats/base/dists/lognormal/mean","base.dists.lognormal.median":"@stdlib/stats/base/dists/lognormal/median","base.dists.lognormal.mode":"@stdlib/stats/base/dists/lognormal/mode","base.dists.lognormal.pdf":"@stdlib/stats/base/dists/lognormal/pdf","base.dists.lognormal.quantile":"@stdlib/stats/base/dists/lognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdli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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv index 48ddfda47742..73cbddc160af 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv @@ -1760,7 +1760,8 @@ SECONDS_IN_WEEK,"" secondsInMonth,"secondsInYear" secondsInYear,"secondsInMonth" setConfigurableReadOnly,"setConfigurableReadOnlyAccessor,defineProperty,setReadOnly" -setConfigurableReadOnlyAccessor,"setConfigurableReadOnly,defineProperty,setReadOnlyAccessor" +setConfigurableReadOnlyAccessor,"setConfigurableReadOnly,setConfigurableWriteOnlyAccessor,defineProperty,setReadOnlyAccessor" +setConfigurableWriteOnlyAccessor,"setConfigurableReadOnly,setConfigurableReadOnlyAccessor,defineProperty,setWriteOnlyAccessor" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index f0bd11aa5655..16f1f5a24a7e 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1761,6 +1761,7 @@ secondsInMonth secondsInYear setConfigurableReadOnly setConfigurableReadOnlyAccessor +setConfigurableWriteOnlyAccessor setNonEnumerableProperty setNonEnumerableReadOnly setNonEnumerableReadOnlyAccessor diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/s.js b/lib/node_modules/@stdlib/namespace/lib/namespace/s.js index 2b8c3167ba7e..0b153529879c 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/s.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/s.js @@ -173,6 +173,7 @@ ns.push({ 'type': 'Function', 'related': [ '@stdlib/utils/define-configurable-read-only-accessor', + '@stdlib/utils/define-configurable-read-write-accessor', '@stdlib/utils/define-property', '@stdlib/utils/define-read-only-property' ] @@ -185,11 +186,27 @@ ns.push({ 'type': 'Function', 'related': [ '@stdlib/utils/define-configurable-read-only-property', + '@stdlib/utils/define-configurable-read-write-accessor', + '@stdlib/utils/define-configurable-write-only-accessor', '@stdlib/utils/define-property', '@stdlib/utils/define-read-only-accessor' ] }); +ns.push({ + 'alias': 'setConfigurableWriteOnlyAccessor', + 'path': '@stdlib/utils/define-configurable-write-only-accessor', + 'value': require( '@stdlib/utils/define-configurable-write-only-accessor' ), + 'type': 'Function', + 'related': [ + '@stdlib/utils/define-configurable-read-only-property', + '@stdlib/utils/define-configurable-read-only-accessor', + '@stdlib/utils/define-configurable-read-write-accessor', + '@stdlib/utils/define-property', + '@stdlib/utils/define-write-only-accessor' + ] +}); + ns.push({ 'alias': 'setNonEnumerableProperty', 'path': '@stdlib/utils/define-nonenumerable-property', diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index 173476f568b6..a9e41b043363 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -1761,6 +1761,7 @@ "@stdlib/time/seconds-in-year",secondsInYear "@stdlib/utils/define-configurable-read-only-property",setConfigurableReadOnly "@stdlib/utils/define-configurable-read-only-accessor",setConfigurableReadOnlyAccessor +"@stdlib/utils/define-configurable-write-only-accessor",setConfigurableWriteOnlyAccessor "@stdlib/utils/define-nonenumerable-property",setNonEnumerableProperty "@stdlib/utils/define-nonenumerable-read-only-property",setNonEnumerableReadOnly "@stdlib/utils/define-nonenumerable-read-only-accessor",setNonEnumerableReadOnlyAccessor diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index 072251860706..6205f3f49af9 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ -{"@stdlib/datasets/afinn-96":"AFINN_96","@stdlib/datasets/afinn-111":"AFINN_111","@stdlib/namespace/alias2pkg":"alias2pkg","@stdlib/namespace/alias2related":"alias2related","@stdlib/namespace/aliases":"aliases","@stdlib/buffer/alloc-unsafe":"allocUnsafe","@stdlib/stats/anova1":"anova1","@stdlib/datasets/anscombes-quartet":"ANSCOMBES_QUARTET","@stdlib/utils/any":"any","@stdlib/utils/any-by":"anyBy","@stdlib/utils/async/any-by":"anyByAsync","@stdlib/utils/any-by-right":"anyByRight","@stdlib/utils/async/any-by-right":"anyByRightAsync","@stdlib/constants/math/float64-apery":"APERY","@stdlib/utils/append":"append","@stdlib/os/arch":"ARCH","@stdlib/utils/argument-function":"argumentFunction","@stdlib/process/argv":"ARGV","@stdlib/ndarray/array":"array","@stdlib/buffer/from-array":"array2buffer","@stdlib/array/to-iterator":"array2iterator","@stdlib/array/to-iterator-right":"array2iteratorRight","@stdlib/array/buffer":"ArrayBuffer","@stdlib/buffer/from-arraybuffer":"arraybuffer2buffer","@stdlib/array/ctors":"arrayCtors","@stdlib/array/dtype":"arrayDataType","@stdlib/array/dtypes":"arrayDataTypes","@stdlib/array/min-dtype":"arrayMinDataType","@stdlib/array/next-dtype":"arrayNextDataType","@stdlib/array/promotion-rules":"arrayPromotionRules","@stdlib/array/safe-casts":"arraySafeCasts","@stdlib/array/same-kind-casts":"arraySameKindCasts","@stdlib/array/shape":"arrayShape","@stdlib/streams/node/from-array":"arrayStream","@stdlib/array/to-view-iterator":"arrayview2iterator","@stdlib/array/to-view-iterator-right":"arrayview2iteratorRight","@stdlib/symbol/async-iterator":"AsyncIteratorSymbol","@stdlib/stats/bartlett-test":"bartlettTest","@stdlib/math/base/special/abs":"base.abs","@stdlib/math/base/special/abs2":"base.abs2","@stdlib/math/base/utils/absolute-difference":"base.absdiff","@stdlib/math/base/special/int32-abs":"base.absInt32","@stdlib/math/base/special/acos":"base.acos","@stdlib/math/base/special/acosh":"base.acosh","@stdlib/math/base/special/acoth":"base.acoth","@stdlib/math/base/special/acovercos":"base.acovercos","@stdlib/math/base/special/acoversin":"base.acoversin","@stdlib/math/base/special/ahavercos":"base.ahavercos","@stdlib/math/base/special/ahaversin":"base.ahaversin","@stdlib/math/base/special/asin":"base.asin","@stdlib/math/base/special/asinh":"base.asinh","@stdlib/math/base/special/atan":"base.atan","@stdlib/math/base/special/atan2":"base.atan2","@stdlib/math/base/special/atanh":"base.atanh","@stdlib/math/base/special/avercos":"base.avercos","@stdlib/math/base/special/aversin":"base.aversin","@stdlib/math/base/special/bernoulli":"base.bernoulli","@stdlib/math/base/special/besselj0":"base.besselj0","@stdlib/math/base/special/besselj1":"base.besselj1","@stdlib/math/base/special/bessely0":"base.bessely0","@stdlib/math/base/special/bessely1":"base.bessely1","@stdlib/math/base/special/beta":"base.beta","@stdlib/math/base/special/betainc":"base.betainc","@stdlib/math/base/special/betaincinv":"base.betaincinv","@stdlib/math/base/special/betaln":"base.betaln","@stdlib/math/base/special/binet":"base.binet","@stdlib/math/base/special/binomcoef":"base.binomcoef","@stdlib/math/base/special/binomcoefln":"base.binomcoefln","@stdlib/math/base/special/boxcox":"base.boxcox","@stdlib/math/base/special/boxcox1p":"base.boxcox1p","@stdlib/math/base/special/boxcox1pinv":"base.boxcox1pinv","@stdlib/math/base/special/boxcoxinv":"base.boxcoxinv","@stdlib/math/base/complex/abs":"base.cabs","@stdlib/math/base/complex/abs2":"base.cabs2","@stdlib/math/base/complex/add":"base.cadd","@stdlib/math/base/special/cbrt":"base.cbrt","@stdlib/math/base/complex/ceil":"base.cceil","@stdlib/math/base/complex/ceiln":"base.cceiln","@stdlib/math/base/complex/cis":"base.ccis","@stdlib/math/base/complex/divide":"base.cdiv","@stdlib/math/base/special/ceil":"base.ceil","@stdlib/math/base/special/ceil2":"base.ceil2","@stdlib/math/base/special/ceil10":"base.ceil10","@stdlib/math/base/special/ceilb":"base.ceilb","@stdlib/math/base/special/ceiln":"base.ceiln","@stdlib/math/base/special/ceilsd":"base.ceilsd","@stdlib/math/base/complex/exp":"base.cexp","@stdlib/math/base/complex/flipsign":"base.cflipsign","@stdlib/math/base/complex/floor":"base.cfloor","@stdlib/math/base/complex/floorn":"base.cfloorn","@stdlib/math/base/complex/inv":"base.cinv","@stdlib/math/base/special/clamp":"base.clamp","@stdlib/math/base/complex/multiply":"base.cmul","@stdlib/math/base/complex/negate":"base.cneg","@stdlib/math/base/tools/continued-fraction":"base.continuedFraction","@stdlib/math/base/special/copysign":"base.copysign","@stdlib/math/base/special/cos":"base.cos","@stdlib/math/base/special/cosh":"base.cosh","@stdlib/math/base/special/cosm1":"base.cosm1","@stdlib/math/base/special/cospi":"base.cospi","@stdlib/math/base/special/covercos":"base.covercos","@stdlib/math/base/special/coversin":"base.coversin","@stdlib/math/base/complex/phase":"base.cphase","@stdlib/math/base/complex/polar":"base.cpolar","@stdlib/math/base/complex/round":"base.cround","@stdlib/math/base/com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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv index 6b4d1790476d..a85756659aa7 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv @@ -1760,7 +1760,8 @@ "@stdlib/time/seconds-in-month","@stdlib/time/seconds-in-year" "@stdlib/time/seconds-in-year","@stdlib/time/seconds-in-month" "@stdlib/utils/define-configurable-read-only-property","@stdlib/utils/define-configurable-read-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-read-only-property" -"@stdlib/utils/define-configurable-read-only-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-property,@stdlib/utils/define-read-only-accessor" +"@stdlib/utils/define-configurable-read-only-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-configurable-write-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-read-only-accessor" +"@stdlib/utils/define-configurable-write-only-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-configurable-read-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-write-only-accessor" "@stdlib/utils/define-nonenumerable-property","@stdlib/utils/define-nonenumerable-read-only-accessor,@stdlib/utils/define-nonenumerable-read-only-property,@stdlib/utils/define-nonenumerable-read-write-accessor,@stdlib/utils/define-nonenumerable-write-only-accessor,@stdlib/utils/define-read-only-property" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index 46ebb0fc946c..f22010fc8ac5 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -1778,6 +1778,7 @@ var db = { "secondsInYear": "num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n", "setConfigurableReadOnly": "obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", "setConfigurableReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", + "setConfigurableWriteOnlyAccessor": "obj = {};\nval = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n", "setNonEnumerableProperty": "obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n", "setNonEnumerableReadOnly": "obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", "setNonEnumerableReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index 9f2bfe8f4bf0..63d6ed478100 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -1778,7 +1778,8 @@ var db = { "secondsInMonth": "\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n", "secondsInYear": "\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n", "setConfigurableReadOnly": "\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, defineProperty, setReadOnly\n", - "setConfigurableReadOnlyAccessor": "\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, defineProperty, setReadOnlyAccessor\n", + "setConfigurableReadOnlyAccessor": "\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n", + "setConfigurableWriteOnlyAccessor": "\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, defineProperty, setWriteOnlyAccessor\n", "setNonEnumerableProperty": "\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", "setNonEnumerableReadOnly": "\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", "setNonEnumerableReadOnlyAccessor": "\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n", From c1ab594ee8f854f03214375c19bfd46a12267348 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 17:52:37 -0700 Subject: [PATCH 082/142] Fix enumerability --- .../utils/define-configurable-write-only-accessor/lib/main.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/main.js b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/main.js index 0becf92cadd7..95a21119ff39 100644 --- a/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/main.js +++ b/lib/node_modules/@stdlib/utils/define-configurable-write-only-accessor/lib/main.js @@ -47,7 +47,7 @@ var defineProperty = require( '@stdlib/utils/define-property' ); function setConfigurableWriteOnlyAccessor( obj, prop, setter ) { // eslint-disable-line id-length defineProperty( obj, prop, { 'configurable': true, - 'enumerable': false, + 'enumerable': true, 'set': setter }); } From 878fdfcee5cceb5cb937b9e9547724b7c3bfd718 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 18:06:32 -0700 Subject: [PATCH 083/142] Run examples in strict mode --- .../remark/plugins/remark-run-javascript-examples/lib/runner.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/_tools/remark/plugins/remark-run-javascript-examples/lib/runner.js b/lib/node_modules/@stdlib/_tools/remark/plugins/remark-run-javascript-examples/lib/runner.js index 3d9feafddef8..fe9e7e41a2f4 100644 --- a/lib/node_modules/@stdlib/_tools/remark/plugins/remark-run-javascript-examples/lib/runner.js +++ b/lib/node_modules/@stdlib/_tools/remark/plugins/remark-run-javascript-examples/lib/runner.js @@ -219,7 +219,7 @@ function factory( options ) { if ( UFLG ) { if ( FIRST === null ) { debug( 'Caching block contents...' ); - FIRST = script; + FIRST = '"use strict";\n\n' + script; } else { // Prepend the first block to all subsequent code blocks: script = FIRST + '\n\n' + script; From aca2cb622b1fde91101d2d97be75693c72afeeb7 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 18:23:10 -0700 Subject: [PATCH 084/142] Add utility to define a configurable read-write accessor --- .../README.md | 122 ++++++++++++++++ .../benchmark/benchmark.js | 61 ++++++++ .../docs/repl.txt | 36 +++++ .../docs/types/index.d.ts | 78 +++++++++++ .../docs/types/test.ts | 70 ++++++++++ .../examples/index.js | 43 ++++++ .../lib/index.js | 58 ++++++++ .../lib/main.js | 70 ++++++++++ .../package.json | 76 ++++++++++ .../test/test.js | 132 ++++++++++++++++++ 10 files changed, 746 insertions(+) create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/README.md create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/examples/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/main.js create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/package.json create mode 100644 lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/test/test.js diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/README.md b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/README.md new file mode 100644 index 000000000000..edaa0e195c86 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/README.md @@ -0,0 +1,122 @@ + + +# Configurable Read-Write Accessor + +> [Define][@stdlib/utils/define-property] a configurable **read-write** accessor. + +
+ +## Usage + + + +```javascript +var setConfigurableReadWriteAccessor = require( '@stdlib/utils/define-configurable-read-write-accessor' ); +``` + +#### setConfigurableReadWriteAccessor( obj, prop, getter, setter ) + +[Defines][@stdlib/utils/define-property] a configurable **read-write** accessor. + + + +```javascript +var word = 'bar'; +var obj = {}; + +function getter() { + return word + ' foo'; +} + +function setter( v ) { + word = v; +} + +setConfigurableReadWriteAccessor( obj, 'foo', getter, setter ); + +var v = obj.foo; +// returns 'bar foo' + +obj.foo = 'beep'; + +v = obj.foo; +// returns 'beep foo' +``` + +
+ + + +
+ +## Notes + +- Configurable read-write accessors are **enumerable**. + +
+ + + +
+ +## Examples + + + + + +```javascript +var setConfigurableReadWriteAccessor = require( '@stdlib/utils/define-configurable-read-write-accessor' ); + +function Foo( name ) { + if ( !(this instanceof Foo) ) { + return new Foo( name ); + } + setConfigurableReadWriteAccessor( this, 'name', getName, setName ); + return this; + + function getName() { + return 'Hello, ' + name; + } + + function setName( v ) { + name = v; + } +} + +var foo = new Foo( 'Grace' ); +console.log( foo.name ); + +foo.name = 'Ada'; +console.log( foo.name ); +``` + +
+ + + +
+ +[@stdlib/utils/define-property]: https://github.com/stdlib-js/stdlib + +
+ + diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/benchmark/benchmark.js b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/benchmark/benchmark.js new file mode 100644 index 000000000000..20ec386a7c03 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/benchmark/benchmark.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var pkg = require( './../package.json' ).name; +var setConfigurableReadWriteAccessor = require( './../lib' ); // eslint-disable-line id-length + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var obj; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + obj = {}; + setConfigurableReadWriteAccessor( obj, 'foo', getter( i.toString() ), setter ); + if ( !isString( obj.foo ) ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( obj.foo ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function getter( v ) { + return get; + + function get() { + return v; + } + } + + function setter( v ) { + obj.foo = v; + } +}); diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/repl.txt b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/repl.txt new file mode 100644 index 000000000000..b70065fa6dca --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/repl.txt @@ -0,0 +1,36 @@ + +{{alias}}( obj, prop, getter, setter ) + Defines a configurable property having read-write accessors. + + Configurable read-write accessors are enumerable. + + Parameters + ---------- + obj: Object + Object on which to define the property. + + prop: string|symbol + Property name. + + getter: Function + Get accessor. + + setter: Function + Set accessor. + + Examples + -------- + > var obj = {}; + > var name = 'bar'; + > function getter() { return name + ' foo'; }; + > function setter( v ) { name = v; }; + > {{alias}}( obj, 'foo', getter, setter ); + > obj.foo + 'bar foo' + > obj.foo = 'beep'; + > obj.foo + 'beep foo' + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/types/index.d.ts b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/types/index.d.ts new file mode 100644 index 000000000000..845e6b7ae024 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/types/index.d.ts @@ -0,0 +1,78 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/// + +import { PropertyName } from '@stdlib/types/object'; + +/** +* Getter function. +* +* @returns property value +*/ +type Getter = () => any; + +/** +* Setter function. +* +* @param value - property value +*/ +type Setter = ( x: any ) => void; + +/** +* Defines a configurable read-write accessor. +* +* ## Notes +* +* - Configurable read-write accessors are **enumerable**. +* +* @param obj - object on which to define property +* @param prop - property name +* @param getter - get accessor +* @param setter - set accessor +* +* @example +* var name = 'bar'; +* var obj = {}; +* +* function getter() { +* return name + ' foo'; +* } +* +* function setter( v ) { +* name = v; +* } +* +* setConfigurableReadWriteAccessor( obj, 'foo', getter, setter ); +* +* var v = obj.foo; +* // returns 'bar foo' +* +* obj.foo = 'beep'; +* +* v = obj.foo; +* // returns 'beep foo' +*/ +declare function setConfigurableReadWriteAccessor( obj: any, prop: PropertyName, getter: Getter, setter: Setter ): void; // tslint:disable-line: max-line-length + + +// EXPORTS // + +export = setConfigurableReadWriteAccessor; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/types/test.ts b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/types/test.ts new file mode 100644 index 000000000000..db943244236d --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/docs/types/test.ts @@ -0,0 +1,70 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import setConfigurableReadWriteAccessor = require( './index' ); + + +// TESTS // + +// The function returns `undefined`... +{ + setConfigurableReadWriteAccessor( {}, 'foo', (): string => 'beep', ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectType void +} + +// The compiler throws an error if the function is provided a second argument which is not a valid property name... +{ + setConfigurableReadWriteAccessor( {}, true, (): string => 'beep', ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, false, (): string => 'beep', ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, null, (): string => 'beep', ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, undefined, (): string => 'beep', ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, [], (): string => 'beep', ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, {}, (): string => 'beep', ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, ( x: number ): number => x, (): string => 'beep', ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a valid getter... +{ + setConfigurableReadWriteAccessor( {}, 'foo', '5', ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', 5, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', true, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', false, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', null, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', undefined, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', [], ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', {}, ( x: any ): void => { throw new Error( String( x ) ); } ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a valid setter... +{ + setConfigurableReadWriteAccessor( {}, 'foo', (): string => 'beep', '5' ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', (): string => 'beep', 5 ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', (): string => 'beep', true ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', (): string => 'beep', false ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', (): string => 'beep', null ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', (): string => 'beep', undefined ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', (): string => 'beep', [] ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', (): string => 'beep', {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + setConfigurableReadWriteAccessor(); // $ExpectError + setConfigurableReadWriteAccessor( {} ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo' ); // $ExpectError + setConfigurableReadWriteAccessor( {}, 'foo', (): string => 'beep' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/examples/index.js b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/examples/index.js new file mode 100644 index 000000000000..07f1014901dc --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/examples/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var setConfigurableReadWriteAccessor = require( './../lib' ); // eslint-disable-line id-length + +function Foo( name ) { + if ( !(this instanceof Foo) ) { + return new Foo( name ); + } + setConfigurableReadWriteAccessor( this, 'name', getName, setName ); + return this; + + function getName() { + return 'Hello, ' + name; + } + + function setName( v ) { + name = v; + } +} + +var foo = new Foo( 'Grace' ); +console.log( foo.name ); + +foo.name = 'Ada'; +console.log( foo.name ); diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/index.js b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/index.js new file mode 100644 index 000000000000..5449a2c6db5d --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/index.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Define a configurable read-write accessor. +* +* @module @stdlib/utils/define-configurable-read-write-accessor +* +* @example +* var setConfigurableReadWriteAccessor = require( '@stdlib/utils/define-configurable-read-write-accessor' ); +* +* var name = 'bar'; +* var obj = {}; +* +* function getter() { +* return name + ' foo'; +* } +* +* function setter( v ) { +* name = v; +* } +* +* setConfigurableReadWriteAccessor( obj, 'foo', getter, setter ); +* +* var v = obj.foo; +* // returns 'bar foo' +* +* obj.foo = 'beep'; +* +* v = obj.foo; +* // returns 'beep foo' +*/ + +// MODULES // + +var setConfigurableReadWriteAccessor = require( './main.js' ); + + +// EXPORTS // + +module.exports = setConfigurableReadWriteAccessor; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/main.js b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/main.js new file mode 100644 index 000000000000..1b1d5faf8a58 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/main.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var defineProperty = require( '@stdlib/utils/define-property' ); + + +// MAIN // + +/** +* Defines a configurable read-write accessor. +* +* @param {Object} obj - object on which to define the property +* @param {(string|symbol)} prop - property name +* @param {Function} getter - get accessor +* @param {Function} setter - set accessor +* +* @example +* var name = 'bar'; +* var obj = {}; +* +* function getter() { +* return name + ' foo'; +* } +* +* function setter( v ) { +* name = v; +* } +* +* setConfigurableReadWriteAccessor( obj, 'foo', getter, setter ); +* +* var v = obj.foo; +* // returns 'bar foo' +* +* obj.foo = 'beep'; +* +* v = obj.foo; +* // returns 'beep foo' +*/ +function setConfigurableReadWriteAccessor( obj, prop, getter, setter ) { // eslint-disable-line id-length + defineProperty( obj, prop, { + 'configurable': true, + 'enumerable': false, + 'get': getter, + 'set': setter + }); +} + + +// EXPORTS // + +module.exports = setConfigurableReadWriteAccessor; diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/package.json b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/package.json new file mode 100644 index 000000000000..c2fa92f11ce7 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/utils/define-configurable-read-write-accessor", + "version": "0.0.0", + "description": "Define a configurable read-write accessor.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdutils", + "stdutil", + "utilities", + "utility", + "utils", + "util", + "object", + "property", + "define", + "prop", + "read-write", + "read", + "write", + "readable", + "writable", + "configurable", + "accessor", + "get", + "getter", + "set", + "setter", + "enumerable" + ] +} diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/test/test.js b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/test/test.js new file mode 100644 index 000000000000..6c22f86e0824 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/test/test.js @@ -0,0 +1,132 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var objectKeys = require( '@stdlib/utils/keys' ); +var defineProperty = require( '@stdlib/utils/define-property' ); +var propertyDescriptor = require( '@stdlib/utils/property-descriptor' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var setConfigurableReadWriteAccessor = require( './../lib' ); // eslint-disable-line id-length + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.equal( typeof setConfigurableReadWriteAccessor, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function sets a property on a provided object', function test( t ) { + var obj = {}; + var val = 0; + + setConfigurableReadWriteAccessor( obj, 'foo', getter, setter ); + t.equal( obj.foo, val, 'returns expected value' ); + + t.end(); + + function getter() { + return val; + } + + function setter( v ) { + val = v; + } +}); + +tape( 'the read-write property is writable', function test( t ) { + var obj = {}; + var val = 0; + + setConfigurableReadWriteAccessor( obj, 'foo', getter, setter ); + t.equal( obj.foo, 0, 'returns expected value' ); + + obj.foo = 1; + t.equal( obj.foo, 1, 'returns expected value' ); + + t.end(); + + function getter() { + return val; + } + + function setter( v ) { + val = v; + } +}); + +tape( 'the read-write property is configurable', function test( t ) { + var desc; + var obj; + var val; + + val = 0; + + obj = {}; + setConfigurableReadWriteAccessor( obj, 'foo', getter, setter ); + setConfigurableReadWriteAccessor( obj, 'beep', getter, setter ); + + desc = { + 'configurable': true, + 'enumerable': false, + 'get': getter, + 'set': setter + }; + defineProperty( obj, 'foo', desc ); + t.deepEqual( propertyDescriptor( obj, 'foo' ), desc, 'property can be reconfigured' ); + + t.equal( obj.beep, 'bar', 'returns expected value' ); + t.equal( hasOwnProp( obj, 'beep' ), true, 'has property' ); + + // Configurable properties can be deleted... + delete obj.beep; + t.equal( obj.beep, void 0, 'returns expected value' ); + t.equal( hasOwnProp( obj, 'beep' ), false, 'does not have property' ); + t.end(); + + function getter() { + return val; + } + + function setter( v ) { + val = v; + } +}); + +tape( 'the read-write property is enumerable', function test( t ) { + var obj = {}; + var val = 0; + + setConfigurableReadWriteAccessor( obj, 'foo', getter, setter ); + + t.deepEqual( objectKeys( obj ), [ 'foo' ], 'property is enumerable' ); + t.end(); + + function getter() { + return val; + } + + function setter( v ) { + val = v; + } +}); From e164e816254f76f355c312388accf215e7dfede1 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 18:24:34 -0700 Subject: [PATCH 085/142] Update namespace --- lib/node_modules/@stdlib/utils/lib/index.js | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/lib/node_modules/@stdlib/utils/lib/index.js b/lib/node_modules/@stdlib/utils/lib/index.js index 64a3e0895303..a770b4745334 100644 --- a/lib/node_modules/@stdlib/utils/lib/index.js +++ b/lib/node_modules/@stdlib/utils/lib/index.js @@ -261,6 +261,15 @@ setReadOnly( utils, 'setConfigurableReadOnlyAccessor', require( '@stdlib/utils/d */ setReadOnly( utils, 'setConfigurableReadOnly', require( '@stdlib/utils/define-configurable-read-only-property' ) ); +/** +* @name setConfigurableReadWriteAccessor +* @memberof utils +* @readonly +* @type {Function} +* @see {@link module:@stdlib/utils/define-configurable-read-write-accessor} +*/ +setReadOnly( utils, 'setConfigurableReadWriteAccessor', require( '@stdlib/utils/define-configurable-read-write-accessor' ) ); + /** * @name setConfigurableWriteOnlyAccessor * @memberof utils From 4feecf11d58d2ddc155646c40a4ed53a2554f5b4 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 18:25:33 -0700 Subject: [PATCH 086/142] Update namespace --- .../@stdlib/namespace/alias2pkg/data/data.csv | 1 + .../@stdlib/namespace/alias2pkg/data/data.json | 2 +- .../@stdlib/namespace/alias2related/data/data.csv | 7 ++++--- .../@stdlib/namespace/alias2related/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.txt | 1 + .../@stdlib/namespace/lib/namespace/s.js | 14 ++++++++++++++ .../@stdlib/namespace/pkg2alias/data/data.csv | 1 + .../@stdlib/namespace/pkg2alias/data/data.json | 2 +- .../@stdlib/namespace/pkg2related/data/data.csv | 7 ++++--- .../@stdlib/namespace/pkg2related/data/data.json | 2 +- .../@stdlib/repl/code-blocks/lib/db.js | 1 + lib/node_modules/@stdlib/repl/help/lib/db.js | 7 ++++--- 13 files changed, 35 insertions(+), 14 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index 7aecabbf1ca2..ed955b61cff6 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1761,6 +1761,7 @@ secondsInMonth,"@stdlib/time/seconds-in-month" secondsInYear,"@stdlib/time/seconds-in-year" setConfigurableReadOnly,"@stdlib/utils/define-configurable-read-only-property" setConfigurableReadOnlyAccessor,"@stdlib/utils/define-configurable-read-only-accessor" +setConfigurableReadWriteAccessor,"@stdlib/utils/define-configurable-read-write-accessor" setConfigurableWriteOnlyAccessor,"@stdlib/utils/define-configurable-write-only-accessor" setNonEnumerableProperty,"@stdlib/utils/define-nonenumerable-property" setNonEnumerableReadOnly,"@stdlib/utils/define-nonenumerable-read-only-property" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index cb5c1e3f8077..155cf0e13550 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ 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araswamy/variance","base.dists.laplace.cdf":"@stdlib/stats/base/dists/laplace/cdf","base.dists.laplace.entropy":"@stdlib/stats/base/dists/laplace/entropy","base.dists.laplace.kurtosis":"@stdlib/stats/base/dists/laplace/kurtosis","base.dists.laplace.Laplace":"@stdlib/stats/base/dists/laplace/ctor","base.dists.laplace.logcdf":"@stdlib/stats/base/dists/laplace/logcdf","base.dists.laplace.logpdf":"@stdlib/stats/base/dists/laplace/logpdf","base.dists.laplace.mean":"@stdlib/stats/base/dists/laplace/mean","base.dists.laplace.median":"@stdlib/stats/base/dists/laplace/median","base.dists.laplace.mgf":"@stdlib/stats/base/dists/laplace/mgf","base.dists.laplace.mode":"@stdlib/stats/base/dists/laplace/mode","base.dists.laplace.pdf":"@stdlib/stats/base/dists/laplace/pdf","base.dists.laplace.quantile":"@stdlib/stats/base/dists/laplace/quantile","base.dists.laplace.skewness":"@stdlib/stats/base/dists/laplace/skewness","base.dists.laplace.stdev":"@stdlib/stats/base/dists/laplace/stdev","base.dists.laplace.variance":"@stdlib/stats/base/dists/laplace/variance","base.dists.levy.cdf":"@stdlib/stats/base/dists/levy/cdf","base.dists.levy.entropy":"@stdlib/stats/base/dists/levy/entropy","base.dists.levy.Levy":"@stdlib/stats/base/dists/levy/ctor","base.dists.levy.logcdf":"@stdlib/stats/base/dists/levy/logcdf","base.dists.levy.logpdf":"@stdlib/stats/base/dists/levy/logpdf","base.dists.levy.mean":"@stdlib/stats/base/dists/levy/mean","base.dists.levy.median":"@stdlib/stats/base/dists/levy/median","base.dists.levy.mode":"@stdlib/stats/base/dists/levy/mode","base.dists.levy.pdf":"@stdlib/stats/base/dists/levy/pdf","base.dists.levy.quantile":"@stdlib/stats/base/dists/levy/quantile","base.dists.levy.stdev":"@stdlib/stats/base/dists/levy/stdev","base.dists.levy.variance":"@stdlib/stats/base/dists/levy/variance","base.dists.logistic.cdf":"@stdlib/stats/base/dists/logistic/cdf","base.dists.logistic.entropy":"@stdlib/stats/base/dists/logistic/entropy","base.dists.logistic.kurtosis":"@stdlib/stats/base/dists/logistic/kurtosis","base.dists.logistic.logcdf":"@stdlib/stats/base/dists/logistic/logcdf","base.dists.logistic.Logistic":"@stdlib/stats/base/dists/logistic/ctor","base.dists.logistic.logpdf":"@stdlib/stats/base/dists/logistic/logpdf","base.dists.logistic.mean":"@stdlib/stats/base/dists/logistic/mean","base.dists.logistic.median":"@stdlib/stats/base/dists/logistic/median","base.dists.logistic.mgf":"@stdlib/stats/base/dists/logistic/mgf","base.dists.logistic.mode":"@stdlib/stats/base/dists/logistic/mode","base.dists.logistic.pdf":"@stdlib/stats/base/dists/logistic/pdf","base.dists.logistic.quantile":"@stdlib/stats/base/dists/logistic/quantile","base.dists.logistic.skewness":"@stdlib/stats/base/dists/logistic/skewness","base.dists.logistic.stdev":"@stdlib/stats/base/dists/logistic/stdev","base.dists.logistic.variance":"@stdlib/stats/base/dists/logistic/variance","base.dists.lognormal.cdf":"@stdlib/stats/base/dists/lognormal/cdf","base.dists.lognormal.entropy":"@stdlib/stats/base/dists/lognormal/entropy","base.dists.lognormal.kurtosis":"@stdlib/stats/base/dists/lognormal/kurtosis","base.dists.lognormal.LogNormal":"@stdlib/stats/base/dists/lognormal/ctor","base.dists.lognormal.logpdf":"@stdlib/stats/base/dists/lognormal/logpdf","base.dists.lognormal.mean":"@stdlib/stats/base/dists/lognormal/mean","base.dists.lognormal.median":"@stdlib/stats/base/dists/lognormal/median","base.dists.lognormal.mode":"@stdlib/stats/base/dists/lognormal/mode","base.dists.lognormal.pdf":"@stdlib/stats/base/dists/lognormal/pdf","base.dists.lognormal.quantile":"@stdlib/stats/base/dists/lognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdli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araswamy/variance","base.dists.laplace.cdf":"@stdlib/stats/base/dists/laplace/cdf","base.dists.laplace.entropy":"@stdlib/stats/base/dists/laplace/entropy","base.dists.laplace.kurtosis":"@stdlib/stats/base/dists/laplace/kurtosis","base.dists.laplace.Laplace":"@stdlib/stats/base/dists/laplace/ctor","base.dists.laplace.logcdf":"@stdlib/stats/base/dists/laplace/logcdf","base.dists.laplace.logpdf":"@stdlib/stats/base/dists/laplace/logpdf","base.dists.laplace.mean":"@stdlib/stats/base/dists/laplace/mean","base.dists.laplace.median":"@stdlib/stats/base/dists/laplace/median","base.dists.laplace.mgf":"@stdlib/stats/base/dists/laplace/mgf","base.dists.laplace.mode":"@stdlib/stats/base/dists/laplace/mode","base.dists.laplace.pdf":"@stdlib/stats/base/dists/laplace/pdf","base.dists.laplace.quantile":"@stdlib/stats/base/dists/laplace/quantile","base.dists.laplace.skewness":"@stdlib/stats/base/dists/laplace/skewness","base.dists.laplace.stdev":"@stdlib/stats/base/dists/laplace/stdev","base.dists.laplace.variance":"@stdlib/stats/base/dists/laplace/variance","base.dists.levy.cdf":"@stdlib/stats/base/dists/levy/cdf","base.dists.levy.entropy":"@stdlib/stats/base/dists/levy/entropy","base.dists.levy.Levy":"@stdlib/stats/base/dists/levy/ctor","base.dists.levy.logcdf":"@stdlib/stats/base/dists/levy/logcdf","base.dists.levy.logpdf":"@stdlib/stats/base/dists/levy/logpdf","base.dists.levy.mean":"@stdlib/stats/base/dists/levy/mean","base.dists.levy.median":"@stdlib/stats/base/dists/levy/median","base.dists.levy.mode":"@stdlib/stats/base/dists/levy/mode","base.dists.levy.pdf":"@stdlib/stats/base/dists/levy/pdf","base.dists.levy.quantile":"@stdlib/stats/base/dists/levy/quantile","base.dists.levy.stdev":"@stdlib/stats/base/dists/levy/stdev","base.dists.levy.variance":"@stdlib/stats/base/dists/levy/variance","base.dists.logistic.cdf":"@stdlib/stats/base/dists/logistic/cdf","base.dists.logistic.entropy":"@stdlib/stats/base/dists/logistic/entropy","base.dists.logistic.kurtosis":"@stdlib/stats/base/dists/logistic/kurtosis","base.dists.logistic.logcdf":"@stdlib/stats/base/dists/logistic/logcdf","base.dists.logistic.Logistic":"@stdlib/stats/base/dists/logistic/ctor","base.dists.logistic.logpdf":"@stdlib/stats/base/dists/logistic/logpdf","base.dists.logistic.mean":"@stdlib/stats/base/dists/logistic/mean","base.dists.logistic.median":"@stdlib/stats/base/dists/logistic/median","base.dists.logistic.mgf":"@stdlib/stats/base/dists/logistic/mgf","base.dists.logistic.mode":"@stdlib/stats/base/dists/logistic/mode","base.dists.logistic.pdf":"@stdlib/stats/base/dists/logistic/pdf","base.dists.logistic.quantile":"@stdlib/stats/base/dists/logistic/quantile","base.dists.logistic.skewness":"@stdlib/stats/base/dists/logistic/skewness","base.dists.logistic.stdev":"@stdlib/stats/base/dists/logistic/stdev","base.dists.logistic.variance":"@stdlib/stats/base/dists/logistic/variance","base.dists.lognormal.cdf":"@stdlib/stats/base/dists/lognormal/cdf","base.dists.lognormal.entropy":"@stdlib/stats/base/dists/lognormal/entropy","base.dists.lognormal.kurtosis":"@stdlib/stats/base/dists/lognormal/kurtosis","base.dists.lognormal.LogNormal":"@stdlib/stats/base/dists/lognormal/ctor","base.dists.lognormal.logpdf":"@stdlib/stats/base/dists/lognormal/logpdf","base.dists.lognormal.mean":"@stdlib/stats/base/dists/lognormal/mean","base.dists.lognormal.median":"@stdlib/stats/base/dists/lognormal/median","base.dists.lognormal.mode":"@stdlib/stats/base/dists/lognormal/mode","base.dists.lognormal.pdf":"@stdlib/stats/base/dists/lognormal/pdf","base.dists.lognormal.quantile":"@stdlib/stats/base/dists/lognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdli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at64-sqrt-half","SQRT_HALF_PI":"@stdlib/constants/math/float64-sqrt-half-pi","SQRT_PHI":"@stdlib/constants/math/float64-sqrt-phi","SQRT_PI":"@stdlib/constants/math/float64-sqrt-pi","SQRT_THREE":"@stdlib/constants/math/float64-sqrt-three","SQRT_TWO":"@stdlib/constants/math/float64-sqrt-two","SQRT_TWO_PI":"@stdlib/constants/math/float64-sqrt-two-pi","Stack":"@stdlib/utils/stack","startcase":"@stdlib/string/startcase","startsWith":"@stdlib/string/starts-with","STOPWORDS_EN":"@stdlib/datasets/stopwords-en","stridedarray2iterator":"@stdlib/array/to-strided-iterator","stridedArrayStream":"@stdlib/streams/node/from-strided-array","string2buffer":"@stdlib/buffer/from-string","sub2ind":"@stdlib/ndarray/sub2ind","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-multi-hop-sensor-network","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-single-hop-sensor-network","Symbol":"@stdlib/symbol/ctor","tabulate":"@stdlib/utils/tabulate","tabulateBy":"@stdlib/utils/tabulate-by","tabulateByAsync":"@stdlib/utils/async/tabulate-by","tic":"@stdlib/time/tic","timeit":"@stdlib/utils/timeit","tmpdir":"@stdlib/os/tmpdir","toc":"@stdlib/time/toc","tokenize":"@stdlib/nlp/tokenize","transformStream":"@stdlib/streams/node/transform","trim":"@stdlib/string/trim","trycatch":"@stdlib/utils/try-catch","trycatchAsync":"@stdlib/utils/async/try-catch","tryFunction":"@stdlib/utils/try-function","tryRequire":"@stdlib/utils/try-require","trythen":"@stdlib/utils/try-then","trythenAsync":"@stdlib/utils/async/try-then","ttest":"@stdlib/stats/ttest","ttest2":"@stdlib/stats/ttest2","TWO_PI":"@stdlib/constants/math/float64-two-pi","typedarray":"@stdlib/array/typed","typedarray2json":"@stdlib/array/to-json","typedarrayComplexCtors":"@stdlib/array/typed-complex-ctors","typedarrayComplexDataTypes":"@stdlib/array/typed-complex-dtypes","typedarrayCtors":"@stdlib/array/typed-ctors","typedarrayDataTypes":"@stdlib/array/typed-dtypes","typedarraypool":"@stdlib/array/pool","typemax":"@stdlib/utils/type-max","typemin":"@stdlib/utils/type-min","typeOf":"@stdlib/utils/type-of","UINT8_MAX":"@stdlib/constants/math/uint8-max","UINT8_NUM_BYTES":"@stdlib/constants/math/uint8-num-bytes","Uint8Array":"@stdlib/array/uint8","Uint8ClampedArray":"@stdlib/array/uint8c","UINT16_MAX":"@stdlib/constants/math/uint16-max","UINT16_NUM_BYTES":"@stdlib/constants/math/uint16-num-bytes","Uint16Array":"@stdlib/array/uint16","UINT32_MAX":"@stdlib/constants/math/uint32-max","UINT32_NUM_BYTES":"@stdlib/constants/math/uint32-num-bytes","Uint32Array":"@stdlib/array/uint32","umask":"@stdlib/process/umask","uncapitalize":"@stdlib/string/uncapitalize","uncapitalizeKeys":"@stdlib/utils/uncapitalize-keys","uncurry":"@stdlib/utils/uncurry","uncurryRight":"@stdlib/utils/uncurry-right","UNICODE_MAX":"@stdlib/constants/string/unicode-max","UNICODE_MAX_BMP":"@stdlib/constants/string/unicode-max-bmp","UnicodeColumnChartSparkline":"@stdlib/plot/sparklines/unicode/column","UnicodeLineChartSparkline":"@stdlib/plot/sparklines/unicode/line","UnicodeSparkline":"@stdlib/plot/sparklines/unicode","UnicodeTristateChartSparkline":"@stdlib/plot/sparklines/unicode/tristate","UnicodeUpDownChartSparkline":"@stdlib/plot/sparklines/unicode/up-down","UnicodeWinLossChartSparkline":"@stdlib/plot/sparklines/unicode/win-loss","unlink":"@stdlib/fs/unlink","unshift":"@stdlib/utils/unshift","until":"@stdlib/utils/until","untilAsync":"@stdlib/utils/async/until","untilEach":"@stdlib/utils/until-each","untilEachRight":"@stdlib/utils/until-each-right","unzip":"@stdlib/utils/unzip","uppercase":"@stdlib/string/uppercase","uppercaseKeys":"@stdlib/utils/uppercase-keys","US_STATES_ABBR":"@stdlib/datasets/us-states-abbr","US_STATES_CAPITALS":"@stdlib/datasets/us-states-capitals","US_STATES_CAPITALS_NAMES":"@stdlib/datasets/us-states-capitals-names","US_STATES_NAMES":"@stdlib/datasets/us-states-names","US_STATES_NAMES_CAPITALS":"@stdlib/datasets/us-states-names-capitals","utf16ToUTF8Array":"@stdlib/string/utf16-to-utf8-array","vartest":"@stdlib/stats/vartest","waterfall":"@stdlib/utils/async/series-waterfall","whileAsync":"@stdlib/utils/async/while","whileEach":"@stdlib/utils/while-each","whileEachRight":"@stdlib/utils/while-each-right","whilst":"@stdlib/utils/while","writableProperties":"@stdlib/utils/writable-properties","writablePropertiesIn":"@stdlib/utils/writable-properties-in","writablePropertyNames":"@stdlib/utils/writable-property-names","writablePropertyNamesIn":"@stdlib/utils/writable-property-names-in","writablePropertySymbols":"@stdlib/utils/writable-property-symbols","writablePropertySymbolsIn":"@stdlib/utils/writable-property-symbols-in","writeFile":"@stdlib/fs/write-file","zip":"@stdlib/utils/zip","ztest":"@stdlib/stats/ztest","ztest2":"@stdlib/stats/ztest2"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv index 73cbddc160af..1cab98b0c5aa 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv @@ -1759,9 +1759,10 @@ SECONDS_IN_MINUTE,"" SECONDS_IN_WEEK,"" secondsInMonth,"secondsInYear" secondsInYear,"secondsInMonth" -setConfigurableReadOnly,"setConfigurableReadOnlyAccessor,defineProperty,setReadOnly" -setConfigurableReadOnlyAccessor,"setConfigurableReadOnly,setConfigurableWriteOnlyAccessor,defineProperty,setReadOnlyAccessor" -setConfigurableWriteOnlyAccessor,"setConfigurableReadOnly,setConfigurableReadOnlyAccessor,defineProperty,setWriteOnlyAccessor" +setConfigurableReadOnly,"setConfigurableReadOnlyAccessor,setConfigurableReadWriteAccessor,defineProperty,setReadOnly" +setConfigurableReadOnlyAccessor,"setConfigurableReadOnly,setConfigurableReadWriteAccessor,setConfigurableWriteOnlyAccessor,defineProperty,setReadOnlyAccessor" +setConfigurableReadWriteAccessor,"setConfigurableReadOnly,setConfigurableReadOnlyAccessor,setConfigurableWriteOnlyAccessor,defineProperty,setReadWriteAccessor" +setConfigurableWriteOnlyAccessor,"setConfigurableReadOnly,setConfigurableReadOnlyAccessor,setConfigurableReadWriteAccessor,defineProperty,setWriteOnlyAccessor" setNonEnumerableProperty,"setNonEnumerableReadOnlyAccessor,setNonEnumerableReadOnly,setNonEnumerableReadWriteAccessor,setNonEnumerableWriteOnlyAccessor,setReadOnly" setNonEnumerableReadOnly,"setNonEnumerableProperty,setNonEnumerableReadOnlyAccessor,setNonEnumerableReadWriteAccessor,setNonEnumerableWriteOnlyAccessor,setReadOnly" setNonEnumerableReadOnlyAccessor,"setNonEnumerableProperty,setNonEnumerableReadOnly,setNonEnumerableReadWriteAccessor,setNonEnumerableWriteOnlyAccessor,setReadOnlyAccessor" diff --git 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index 16f1f5a24a7e..5699f2a9c9a1 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1761,6 +1761,7 @@ secondsInMonth secondsInYear setConfigurableReadOnly setConfigurableReadOnlyAccessor +setConfigurableReadWriteAccessor setConfigurableWriteOnlyAccessor setNonEnumerableProperty setNonEnumerableReadOnly diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/s.js b/lib/node_modules/@stdlib/namespace/lib/namespace/s.js index 0b153529879c..e89267e2a5c3 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/s.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/s.js @@ -193,6 +193,20 @@ ns.push({ ] }); +ns.push({ + 'alias': 'setConfigurableReadWriteAccessor', + 'path': '@stdlib/utils/define-configurable-read-write-accessor', + 'value': require( '@stdlib/utils/define-configurable-read-write-accessor' ), + 'type': 'Function', + 'related': [ + '@stdlib/utils/define-configurable-read-only-property', + '@stdlib/utils/define-configurable-read-only-accessor', + '@stdlib/utils/define-configurable-write-only-accessor', + '@stdlib/utils/define-property', + '@stdlib/utils/define-read-write-accessor' + ] +}); + ns.push({ 'alias': 'setConfigurableWriteOnlyAccessor', 'path': '@stdlib/utils/define-configurable-write-only-accessor', diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index a9e41b043363..9335fd88132a 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -1761,6 +1761,7 @@ "@stdlib/time/seconds-in-year",secondsInYear "@stdlib/utils/define-configurable-read-only-property",setConfigurableReadOnly "@stdlib/utils/define-configurable-read-only-accessor",setConfigurableReadOnlyAccessor +"@stdlib/utils/define-configurable-read-write-accessor",setConfigurableReadWriteAccessor "@stdlib/utils/define-configurable-write-only-accessor",setConfigurableWriteOnlyAccessor "@stdlib/utils/define-nonenumerable-property",setNonEnumerableProperty "@stdlib/utils/define-nonenumerable-read-only-property",setNonEnumerableReadOnly diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index 6205f3f49af9..4ae61e34b986 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ 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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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lf":"SQRT_HALF","@stdlib/constants/math/float64-sqrt-half-pi":"SQRT_HALF_PI","@stdlib/constants/math/float64-sqrt-phi":"SQRT_PHI","@stdlib/constants/math/float64-sqrt-pi":"SQRT_PI","@stdlib/constants/math/float64-sqrt-three":"SQRT_THREE","@stdlib/constants/math/float64-sqrt-two":"SQRT_TWO","@stdlib/constants/math/float64-sqrt-two-pi":"SQRT_TWO_PI","@stdlib/utils/stack":"Stack","@stdlib/string/startcase":"startcase","@stdlib/string/starts-with":"startsWith","@stdlib/datasets/stopwords-en":"STOPWORDS_EN","@stdlib/array/to-strided-iterator":"stridedarray2iterator","@stdlib/streams/node/from-strided-array":"stridedArrayStream","@stdlib/buffer/from-string":"string2buffer","@stdlib/ndarray/sub2ind":"sub2ind","@stdlib/datasets/suthaharan-multi-hop-sensor-network":"SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","@stdlib/datasets/suthaharan-single-hop-sensor-network":"SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","@stdlib/symbol/ctor":"Symbol","@stdlib/utils/tabulate":"tabulate","@stdlib/utils/tabulate-by":"tabulateBy","@stdlib/utils/async/tabulate-by":"tabulateByAsync","@stdlib/time/tic":"tic","@stdlib/utils/timeit":"timeit","@stdlib/os/tmpdir":"tmpdir","@stdlib/time/toc":"toc","@stdlib/nlp/tokenize":"tokenize","@stdlib/streams/node/transform":"transformStream","@stdlib/string/trim":"trim","@stdlib/utils/try-catch":"trycatch","@stdlib/utils/async/try-catch":"trycatchAsync","@stdlib/utils/try-function":"tryFunction","@stdlib/utils/try-require":"tryRequire","@stdlib/utils/try-then":"trythen","@stdlib/utils/async/try-then":"trythenAsync","@stdlib/stats/ttest":"ttest","@stdlib/stats/ttest2":"ttest2","@stdlib/constants/math/float64-two-pi":"TWO_PI","@stdlib/array/typed":"typedarray","@stdlib/array/to-json":"typedarray2json","@stdlib/array/typed-complex-ctors":"typedarrayComplexCtors","@stdlib/array/typed-complex-dtypes":"typedarrayComplexDataTypes","@stdlib/array/typed-ctors":"typedarrayCtors","@stdlib/array/typed-dtypes":"typedarrayDataTypes","@stdlib/array/pool":"typedarraypool","@stdlib/utils/type-max":"typemax","@stdlib/utils/type-min":"typemin","@stdlib/utils/type-of":"typeOf","@stdlib/constants/math/uint8-max":"UINT8_MAX","@stdlib/constants/math/uint8-num-bytes":"UINT8_NUM_BYTES","@stdlib/array/uint8":"Uint8Array","@stdlib/array/uint8c":"Uint8ClampedArray","@stdlib/constants/math/uint16-max":"UINT16_MAX","@stdlib/constants/math/uint16-num-bytes":"UINT16_NUM_BYTES","@stdlib/array/uint16":"Uint16Array","@stdlib/constants/math/uint32-max":"UINT32_MAX","@stdlib/constants/math/uint32-num-bytes":"UINT32_NUM_BYTES","@stdlib/array/uint32":"Uint32Array","@stdlib/process/umask":"umask","@stdlib/string/uncapitalize":"uncapitalize","@stdlib/utils/uncapitalize-keys":"uncapitalizeKeys","@stdlib/utils/uncurry":"uncurry","@stdlib/utils/uncurry-right":"uncurryRight","@stdlib/constants/string/unicode-max":"UNICODE_MAX","@stdlib/constants/string/unicode-max-bmp":"UNICODE_MAX_BMP","@stdlib/plot/sparklines/unicode/column":"UnicodeColumnChartSparkline","@stdlib/plot/sparklines/unicode/line":"UnicodeLineChartSparkline","@stdlib/plot/sparklines/unicode":"UnicodeSparkline","@stdlib/plot/sparklines/unicode/tristate":"UnicodeTristateChartSparkline","@stdlib/plot/sparklines/unicode/up-down":"UnicodeUpDownChartSparkline","@stdlib/plot/sparklines/unicode/win-loss":"UnicodeWinLossChartSparkline","@stdlib/fs/unlink":"unlink","@stdlib/utils/unshift":"unshift","@stdlib/utils/until":"until","@stdlib/utils/async/until":"untilAsync","@stdlib/utils/until-each":"untilEach","@stdlib/utils/until-each-right":"untilEachRight","@stdlib/utils/unzip":"unzip","@stdlib/string/uppercase":"uppercase","@stdlib/utils/uppercase-keys":"uppercaseKeys","@stdlib/datasets/us-states-abbr":"US_STATES_ABBR","@stdlib/datasets/us-states-capitals":"US_STATES_CAPITALS","@stdlib/datasets/us-states-capitals-names":"US_STATES_CAPITALS_NAMES","@stdlib/datasets/us-states-names":"US_STATES_NAMES","@stdlib/datasets/us-states-names-capitals":"US_STATES_NAMES_CAPITALS","@stdlib/string/utf16-to-utf8-array":"utf16ToUTF8Array","@stdlib/stats/vartest":"vartest","@stdlib/utils/async/series-waterfall":"waterfall","@stdlib/utils/async/while":"whileAsync","@stdlib/utils/while-each":"whileEach","@stdlib/utils/while-each-right":"whileEachRight","@stdlib/utils/while":"whilst","@stdlib/utils/writable-properties":"writableProperties","@stdlib/utils/writable-properties-in":"writablePropertiesIn","@stdlib/utils/writable-property-names":"writablePropertyNames","@stdlib/utils/writable-property-names-in":"writablePropertyNamesIn","@stdlib/utils/writable-property-symbols":"writablePropertySymbols","@stdlib/utils/writable-property-symbols-in":"writablePropertySymbolsIn","@stdlib/fs/write-file":"writeFile","@stdlib/utils/zip":"zip","@stdlib/stats/ztest":"ztest","@stdlib/stats/ztest2":"ztest2"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv index a85756659aa7..dbda789352c7 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv @@ -1759,9 +1759,10 @@ "@stdlib/constants/time/seconds-in-week","" "@stdlib/time/seconds-in-month","@stdlib/time/seconds-in-year" "@stdlib/time/seconds-in-year","@stdlib/time/seconds-in-month" -"@stdlib/utils/define-configurable-read-only-property","@stdlib/utils/define-configurable-read-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-read-only-property" -"@stdlib/utils/define-configurable-read-only-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-configurable-write-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-read-only-accessor" -"@stdlib/utils/define-configurable-write-only-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-configurable-read-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-write-only-accessor" +"@stdlib/utils/define-configurable-read-only-property","@stdlib/utils/define-configurable-read-only-accessor,@stdlib/utils/define-configurable-read-write-accessor,@stdlib/utils/define-property,@stdlib/utils/define-read-only-property" +"@stdlib/utils/define-configurable-read-only-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-configurable-read-write-accessor,@stdlib/utils/define-configurable-write-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-read-only-accessor" +"@stdlib/utils/define-configurable-read-write-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-configurable-read-only-accessor,@stdlib/utils/define-configurable-write-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-read-write-accessor" +"@stdlib/utils/define-configurable-write-only-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-configurable-read-only-accessor,@stdlib/utils/define-configurable-read-write-accessor,@stdlib/utils/define-property,@stdlib/utils/define-write-only-accessor" "@stdlib/utils/define-nonenumerable-property","@stdlib/utils/define-nonenumerable-read-only-accessor,@stdlib/utils/define-nonenumerable-read-only-property,@stdlib/utils/define-nonenumerable-read-write-accessor,@stdlib/utils/define-nonenumerable-write-only-accessor,@stdlib/utils/define-read-only-property" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index f22010fc8ac5..dbb736ddd50a 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -1778,6 +1778,7 @@ var db = { "secondsInYear": "num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n", "setConfigurableReadOnly": "obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", "setConfigurableReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", + "setConfigurableReadWriteAccessor": "obj = {};\nname = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n", "setConfigurableWriteOnlyAccessor": "obj = {};\nval = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n", "setNonEnumerableProperty": "obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n", "setNonEnumerableReadOnly": "obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index 63d6ed478100..05cafc424d68 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -1777,9 +1777,10 @@ var db = { "SECONDS_IN_WEEK": "\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n", "secondsInMonth": "\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n", "secondsInYear": "\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n", - "setConfigurableReadOnly": "\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, defineProperty, setReadOnly\n", - "setConfigurableReadOnlyAccessor": "\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n", - "setConfigurableWriteOnlyAccessor": "\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, defineProperty, setWriteOnlyAccessor\n", + "setConfigurableReadOnly": "\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n", + "setConfigurableReadOnlyAccessor": "\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n", + "setConfigurableReadWriteAccessor": "\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n", + "setConfigurableWriteOnlyAccessor": "\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n", "setNonEnumerableProperty": "\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", "setNonEnumerableReadOnly": "\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", "setNonEnumerableReadOnlyAccessor": "\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n", From 6303f898ce15a88ea1b8ff1a6a9f704540ebadad Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 18:27:19 -0700 Subject: [PATCH 087/142] Fix enumerability --- .../utils/define-configurable-read-write-accessor/lib/main.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/main.js b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/main.js index 1b1d5faf8a58..2e202f0d00e0 100644 --- a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/main.js +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/lib/main.js @@ -58,7 +58,7 @@ var defineProperty = require( '@stdlib/utils/define-property' ); function setConfigurableReadWriteAccessor( obj, prop, getter, setter ) { // eslint-disable-line id-length defineProperty( obj, prop, { 'configurable': true, - 'enumerable': false, + 'enumerable': true, 'get': getter, 'set': setter }); From ecf2b5ce2976cd9f89450b950a714a8303cfee28 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sat, 16 Mar 2019 18:28:33 -0700 Subject: [PATCH 088/142] Fix expected value --- .../utils/define-configurable-read-write-accessor/test/test.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/test/test.js b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/test/test.js index 6c22f86e0824..bb233c9eff64 100644 --- a/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/test/test.js +++ b/lib/node_modules/@stdlib/utils/define-configurable-read-write-accessor/test/test.js @@ -95,7 +95,7 @@ tape( 'the read-write property is configurable', function test( t ) { defineProperty( obj, 'foo', desc ); t.deepEqual( propertyDescriptor( obj, 'foo' ), desc, 'property can be reconfigured' ); - t.equal( obj.beep, 'bar', 'returns expected value' ); + t.equal( obj.beep, 0, 'returns expected value' ); t.equal( hasOwnProp( obj, 'beep' ), true, 'has property' ); // Configurable properties can be deleted... From 67ce2f0915b5d0a5385306df64cdfb934ad2c5bd Mon Sep 17 00:00:00 2001 From: kgryte Date: Sun, 17 Mar 2019 00:42:04 -0700 Subject: [PATCH 089/142] Add utility to define a memoized object property --- .../utils/define-memoized-property/README.md | 125 +++++ .../benchmark/benchmark.js | 62 +++ .../define-memoized-property/docs/repl.txt | 49 ++ .../docs/types/index.d.ts | 78 +++ .../docs/types/test.ts | 67 +++ .../examples/index.js | 47 ++ .../define-memoized-property/lib/index.js | 53 +++ .../define-memoized-property/lib/main.js | 114 +++++ .../define-memoized-property/package.json | 74 +++ .../define-memoized-property/test/test.js | 447 ++++++++++++++++++ 10 files changed, 1116 insertions(+) create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-property/README.md create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-property/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-property/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-property/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-property/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-property/examples/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-property/lib/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-property/lib/main.js create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-property/package.json create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-property/test/test.js diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/README.md b/lib/node_modules/@stdlib/utils/define-memoized-property/README.md new file mode 100644 index 000000000000..b88384e58e30 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/README.md @@ -0,0 +1,125 @@ + + +# Define Memoized Property + +> [Define][mdn-define-property] a memoized object property. + +
+ +## Usage + +```javascript +var defineMemoizedProperty = require( '@stdlib/utils/define-memoized-property' ); +``` + +#### defineMemoizedProperty( obj, prop, descriptor ) + +[Defines][mdn-define-property] a memoized object property. + +```javascript +var obj = {}; + +function foo() { + return 'bar'; +} + +defineMemoizedProperty( obj, 'foo', { + 'configurable': false, + 'enumerable': true, + 'writable': false, + 'value': foo +}); + +var v = obj.foo; +// returns 'bar' +``` + +A property `descriptor` has the following required properties: + +- **value**: synchronous function whose return value will be memoized and set as the property value. + +A property `descriptor` has the following optional properties: + +- **configurable**: `boolean` indicating if property descriptor can be changed and if the property can be deleted from the provided object. Default: `false`. +- **enumerable**: `boolean` indicating if the property shows up when enumerating object properties. Default: `false`. +- **writable**: `boolean` indicating if the value associated with the property can be changed with an assignment operator. Default: `false`. + +
+ + + +
+ +## Notes + +- Until deferred evaluation, an object property is **configurable**. + +
+ + + +
+ +## Examples + + + +```javascript +var fibonacci = require( '@stdlib/math/base/special/fibonacci' ); +var defineMemoizedProperty = require( '@stdlib/utils/define-memoized-property' ); + +function Foo() { + var self; + if ( !(this instanceof Foo) ) { + return new Foo(); + } + self = this; + defineMemoizedProperty( this, 'fibo', { + 'value': fibo + }); + this.count = 0; + return this; + + function fibo() { + self.count += 1; + return fibonacci( 73 ); + } +} + +var foo = new Foo(); + +var i; +for ( i = 0; i < 10; i++ ) { + console.log( 'F: %d. Count: %d.', foo.fibo, foo.count ); +} +``` + +
+ + + +
+ +[mdn-define-property]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Object/defineProperty + +
+ + diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/benchmark/benchmark.js b/lib/node_modules/@stdlib/utils/define-memoized-property/benchmark/benchmark.js new file mode 100644 index 000000000000..ec7d16cc0b31 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/benchmark/benchmark.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var fromCodePoint = require( '@stdlib/string/from-code-point' ); +var pkg = require( './../package.json' ).name; +var defineMemoizedProperty = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var descriptor; + var obj; + var i; + + descriptor = {}; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + obj = {}; + descriptor.value = f( i ); + defineMemoizedProperty( obj, 'foo', descriptor ); + if ( !isString( obj.foo ) ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( obj.foo ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function f( i ) { + return fcn; + + function fcn() { + return fromCodePoint( 97 + (i%26) ); + } + } +}); diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/docs/repl.txt b/lib/node_modules/@stdlib/utils/define-memoized-property/docs/repl.txt new file mode 100644 index 000000000000..1682d73ccdcc --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/docs/repl.txt @@ -0,0 +1,49 @@ + +{{alias}}( obj, prop, descriptor ) + Defines a memoized object property. + + Parameters + ---------- + obj: Object + Object on which to define the property. + + prop: string|symbol + Property name. + + descriptor: Object + Property descriptor. + + descriptor.configurable: boolean (optional) + Boolean indicating if property descriptor can be changed and if the + property can be deleted from the provided object. Default: false. + + descriptor.enumerable: boolean (optional) + Boolean indicating if the property shows up when enumerating object + properties. Default: false. + + descriptor.writable: boolean (optional) + Boolean indicating if the value associated with the property can be + changed with an assignment operator. Default: false. + + descriptor.value: Function + Synchronous function whose return value will be memoized and set as the + property value. + + Examples + -------- + > var obj = {}; + > function foo() { + ... return 'bar'; + ... }; + > {{alias}}( obj, 'foo', { + ... 'configurable': false, + ... 'enumerable': true, + ... 'writable': false, + ... 'value': foo + ... }); + > obj.foo + 'bar' + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/docs/types/index.d.ts b/lib/node_modules/@stdlib/utils/define-memoized-property/docs/types/index.d.ts new file mode 100644 index 000000000000..39434234e6ce --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/docs/types/index.d.ts @@ -0,0 +1,78 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/// + +import { PropertyName, DataPropertyDescriptor } from '@stdlib/types/object'; + +/** +* Interface describing the property descriptor object for creating a memoized object property. +* +* @example +* function foo() { +* return 'bar'; +* } +* +* var desc: PropertyDescriptor = { +* 'configurable': false, +* 'enumerable': false, +* 'writable': false, +* 'value': foo +* }; +*/ +interface PropertyDescriptor extends DataPropertyDescriptor { + /** + * Returns a memoized property value. + * + * @returns memoized property value + */ + value(): any; +} + +/** +* Defines a memoized object property. +* +* @param obj - object on which to define property +* @param prop - property name +* @param desc - property descriptor +* +* @example +* var obj = {}; +* +* function foo() { +* return 'bar'; +* } +* +* defineMemoizedProperty( obj, 'foo', { +* 'configurable': false, +* 'enumerable': false, +* 'writable': false, +* 'value': foo +* }); +* +* var v = obj.foo; +* // returns 'bar' +*/ +declare function defineMemoizedProperty( obj: any, prop: PropertyName, desc: PropertyDescriptor ): void; // tslint:disable-line: max-line-length + + +// EXPORTS // + +export = defineMemoizedProperty; diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/docs/types/test.ts b/lib/node_modules/@stdlib/utils/define-memoized-property/docs/types/test.ts new file mode 100644 index 000000000000..44b9898d488c --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/docs/types/test.ts @@ -0,0 +1,67 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import defineMemoizedProperty = require( './index' ); + + +// TESTS // + +// The function returns `undefined`... +{ + defineMemoizedProperty( {}, 'foo', { 'value': (): string => 'bar' } ); // $ExpectType void + defineMemoizedProperty( {}, 'foo', { 'configurable': true, 'enumerable': true, 'writable': true, 'value': (): string => 'bar' } ); // $ExpectType void +} + +// The compiler throws an error if the function is provided a second argument which is not a valid property name... +{ + defineMemoizedProperty( {}, true, { 'value': (): string => 'bar' } ); // $ExpectError + defineMemoizedProperty( {}, false, { 'value': (): string => 'bar' } ); // $ExpectError + defineMemoizedProperty( {}, null, { 'value': (): string => 'bar' } ); // $ExpectError + defineMemoizedProperty( {}, undefined, { 'value': (): string => 'bar' } ); // $ExpectError + defineMemoizedProperty( {}, [], { 'value': (): string => 'bar' } ); // $ExpectError + defineMemoizedProperty( {}, {}, { 'value': (): string => 'bar' } ); // $ExpectError + defineMemoizedProperty( {}, ( x: number ): number => x, { 'value': (): string => 'bar' } ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a valid descriptor object... +{ + defineMemoizedProperty( {}, 'foo', '5' ); // $ExpectError + defineMemoizedProperty( {}, 'foo', 5 ); // $ExpectError + defineMemoizedProperty( {}, 'foo', true ); // $ExpectError + defineMemoizedProperty( {}, 'foo', false ); // $ExpectError + defineMemoizedProperty( {}, 'foo', null ); // $ExpectError + defineMemoizedProperty( {}, 'foo', undefined ); // $ExpectError + defineMemoizedProperty( {}, 'foo', [] ); // $ExpectError + defineMemoizedProperty( {}, 'foo', {} ); // $ExpectError + + defineMemoizedProperty( {}, 'foo', { 'configurable': true ); // $ExpectError + defineMemoizedProperty( {}, 'foo', { 'configurable': 'true', 'value': (): string => 'bar' } ); // $ExpectError + + defineMemoizedProperty( {}, 'foo', { 'enumerable': true ); // $ExpectError + defineMemoizedProperty( {}, 'foo', { 'enumerable': 'true', 'value': (): string => 'bar' } ); // $ExpectError + + defineMemoizedProperty( {}, 'foo', { 'writable': true ); // $ExpectError + defineMemoizedProperty( {}, 'foo', { 'writable': 'true', 'value': (): string => 'bar' } ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + defineMemoizedProperty(); // $ExpectError + defineMemoizedProperty( {} ); // $ExpectError + defineMemoizedProperty( {}, 'foo' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/examples/index.js b/lib/node_modules/@stdlib/utils/define-memoized-property/examples/index.js new file mode 100644 index 000000000000..bc240d5d8d7c --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/examples/index.js @@ -0,0 +1,47 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var fibonacci = require( '@stdlib/math/base/special/fibonacci' ); +var defineMemoizedProperty = require( './../lib' ); + +function Foo() { + var self; + if ( !(this instanceof Foo) ) { + return new Foo(); + } + self = this; + defineMemoizedProperty( this, 'fibo', { + 'value': fibo + }); + this.count = 0; + return this; + + function fibo() { + self.count += 1; + return fibonacci( 73 ); + } +} + +var foo = new Foo(); + +var i; +for ( i = 0; i < 10; i++ ) { + console.log( 'F: %d. Count: %d.', foo.fibo, foo.count ); +} diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/lib/index.js b/lib/node_modules/@stdlib/utils/define-memoized-property/lib/index.js new file mode 100644 index 000000000000..b58c1870d85a --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/lib/index.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Define a memoized object property. +* +* @module @stdlib/utils/define-memoized-property +* +* @example +* var defineMemoizedProperty = require( '@stdlib/utils/define-memoized-property' ); +* +* var obj = {}; +* +* function foo() { +* return 'bar'; +* } +* +* defineMemoizedProperty( obj, 'foo', { +* 'configurable': false, +* 'enumerable': false, +* 'writable': false, +* 'value': foo +* }); +* +* var v = obj.foo; +* // returns 'bar' +*/ + +// MODULES // + +var defineMemoizedProperty = require( './main.js' ); + + +// EXPORTS // + +module.exports = defineMemoizedProperty; diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/lib/main.js b/lib/node_modules/@stdlib/utils/define-memoized-property/lib/main.js new file mode 100644 index 000000000000..eb7dcdbfe33f --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/lib/main.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isObject = require( '@stdlib/assert/is-object' ); +var isFunction = require( '@stdlib/assert/is-function' ); +var defineProperty = require( '@stdlib/utils/define-property' ); + + +// MAIN // + +/** +* Defines a memoized object property. +* +* @param {Object} obj - object on which to define the property +* @param {(string|symbol)} prop - property name +* @param {Object} desc - property descriptor +* @param {boolean} [desc.configurable=false] - boolean indicating if the property descriptor can be changed and if the property can be deleted from the provided object +* @param {boolean} [desc.enumerable=false] - boolean indicating if the property shows up when enumerating object properties +* @param {boolean} [desc.writable=false] - boolean indicating if the value associated with the property can be changed with an assignment operator +* @param {Function} desc.value - function whose return value will be memoized +* @throws {TypeError} first argument must be an object +* @throws {TypeError} third argument must be an object +* @throws {TypeError} property descriptor `value` property must be a function +* +* @example +* var obj = {}; +* +* function foo() { +* return 'bar'; +* } +* +* defineMemoizedProperty( obj, 'foo', { +* 'configurable': false, +* 'enumerable': false, +* 'writable': false, +* 'value': foo +* }); +* +* var v = obj.foo; +* // returns 'bar' +*/ +function defineMemoizedProperty( obj, prop, desc ) { + if ( !isObject( obj ) ) { + throw new TypeError( 'invalid argument. First argument must be an object. Value: `' + obj + '`.' ); + } + if ( !isObject( desc ) ) { + throw new TypeError( 'invalid argument. Property descriptor must be an object. Value: `' + desc + '`.' ); + } + if ( !isFunction( desc.value ) ) { + throw new TypeError( 'invalid argument. The `value` property of the property descriptor must be a function. Value: `' + desc.value + '`.' ); + } + // Copy descriptor properties to a new data descriptor object: + desc = { + 'configurable': ( desc.configurable === void 0 ) ? false : desc.configurable, + 'enumerable': ( desc.enumerable === void 0 ) ? false : desc.enumerable, + 'writable': ( desc.writable === void 0 ) ? false : desc.writable, + 'value': desc.value + }; + + // Define a configurable (at least temporarily) accessor property: + defineProperty( obj, prop, { + 'configurable': true, + 'enumerable': desc.enumerable, + 'get': getter, + 'set': ( desc.writable ) ? memoize : void 0 + }); + + /** + * Temporary get accessor. + * + * @private + * @returns {*} property value + */ + function getter() { + var value = desc.value.call( obj ); + memoize( value ); + return value; + } + + /** + * Defines a memoized object property. + * + * @private + * @param {*} value - value to set + */ + function memoize( value ) { + desc.value = value; + defineProperty( obj, prop, desc ); + } +} + + +// EXPORTS // + +module.exports = defineMemoizedProperty; diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/package.json b/lib/node_modules/@stdlib/utils/define-memoized-property/package.json new file mode 100644 index 000000000000..05dcff6a42bf --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/package.json @@ -0,0 +1,74 @@ +{ + "name": "@stdlib/utils/define-memoized-property", + "version": "0.0.0", + "description": "Define a memoized object property.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdutils", + "stdutil", + "utilities", + "utility", + "utils", + "util", + "object", + "property", + "define", + "set", + "value", + "prop", + "descriptor", + "writable", + "configurable", + "memoized", + "memoize", + "deferred", + "defer", + "lazy" + ] +} diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/test/test.js b/lib/node_modules/@stdlib/utils/define-memoized-property/test/test.js new file mode 100644 index 000000000000..20a1d0fffe88 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/test/test.js @@ -0,0 +1,447 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var noop = require( '@stdlib/utils/noop' ); +var objectKeys = require( '@stdlib/utils/keys' ); +var propertyDescriptor = require( '@stdlib/utils/property-descriptor' ); +var isWritableProperty = require( '@stdlib/assert/is-writable-property' ); +var isConfigurableProperty = require( '@stdlib/assert/is-configurable-property' ); +var defineMemoizedProperty = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.equal( typeof defineMemoizedProperty, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not an object', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0 + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + defineMemoizedProperty( value, 'foo', { + 'value': noop + }); + }; + } +}); + +tape( 'the function throws an error if provided a third argument which is not an object', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0 + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + defineMemoizedProperty( {}, 'foo', value ); + }; + } +}); + +tape( 'the function throws an error if provided property descriptor having a `value` property which is not a function', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + defineMemoizedProperty( {}, 'foo', { + 'value': value + }); + }; + } +}); + +tape( 'the function sets a memoized property on a provided object', function test( t ) { + var expected; + var count; + var obj; + var i; + + obj = {}; + count = 0; + + defineMemoizedProperty( obj, 'foo', { + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + for ( i = 0; i < 10; i++ ) { + t.equal( obj.foo, 'bar', 'returns expected value' ); + t.equal( count, 1, 'returns expected value' ); + } + expected = { + 'configurable': false, + 'enumerable': false, + 'writable': false, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + + obj = {}; + count = 0; + + defineMemoizedProperty( obj, 'foo', { + 'configurable': false, + 'enumerable': true, + 'writable': true, + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + for ( i = 0; i < 10; i++ ) { + t.equal( obj.foo, 'bar', 'returns expected value' ); + t.equal( count, 1, 'returns expected value' ); + } + expected = { + 'configurable': false, + 'enumerable': true, + 'writable': true, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + count += 1; + return 'bar'; + } +}); + +tape( 'by default, the function sets a non-enumerable memoized property on a provided object', function test( t ) { + var expected; + var obj; + + obj = {}; + + defineMemoizedProperty( obj, 'foo', { + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.deepEqual( objectKeys( obj ), [], 'property is not enumerable' ); + + t.equal( obj.foo, 'bar', 'returns expected value' ); + t.deepEqual( objectKeys( obj ), [], 'property is not enumerable' ); + + expected = { + 'configurable': false, + 'enumerable': false, + 'writable': false, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + return 'bar'; + } +}); + +tape( 'the function supports setting an enumerable memoized property on a provided object', function test( t ) { + var expected; + var obj; + + obj = {}; + + defineMemoizedProperty( obj, 'foo', { + 'enumerable': true, + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.deepEqual( objectKeys( obj ), [ 'foo' ], 'property is enumerable' ); + + t.equal( obj.foo, 'bar', 'returns expected value' ); + t.deepEqual( objectKeys( obj ), [ 'foo' ], 'property is enumerable' ); + + expected = { + 'configurable': false, + 'enumerable': true, + 'writable': false, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + return 'bar'; + } +}); + +tape( 'the function supports setting a non-enumerable memoized property on a provided object', function test( t ) { + var expected; + var obj; + + obj = {}; + + defineMemoizedProperty( obj, 'foo', { + 'enumerable': false, + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.deepEqual( objectKeys( obj ), [], 'property is not enumerable' ); + + t.equal( obj.foo, 'bar', 'returns expected value' ); + t.deepEqual( objectKeys( obj ), [], 'property is not enumerable' ); + + expected = { + 'configurable': false, + 'enumerable': false, + 'writable': false, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + return 'bar'; + } +}); + +tape( 'by default, the function sets a non-writable memoized property on a provided object', function test( t ) { + var expected; + var obj; + + obj = {}; + + defineMemoizedProperty( obj, 'foo', { + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.equal( isWritableProperty( obj, 'foo' ), false, 'is not writable' ); + t.equal( obj.foo, 'bar', 'returns expected value' ); + + expected = { + 'configurable': false, + 'enumerable': false, + 'writable': false, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + return 'bar'; + } +}); + +tape( 'the function supports setting a writable memoized property on a provided object', function test( t ) { + var expected; + var obj; + + obj = {}; + + defineMemoizedProperty( obj, 'foo', { + 'writable': true, + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.equal( isWritableProperty( obj, 'foo' ), true, 'is writable' ); + t.equal( obj.foo, 'bar', 'returns expected value' ); + + expected = { + 'configurable': false, + 'enumerable': false, + 'writable': true, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + return 'bar'; + } +}); + +tape( 'the function supports setting a non-writable memoized property on a provided object', function test( t ) { + var expected; + var obj; + + obj = {}; + + defineMemoizedProperty( obj, 'foo', { + 'writable': false, + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.equal( isWritableProperty( obj, 'foo' ), false, 'is not writable' ); + t.equal( obj.foo, 'bar', 'returns expected value' ); + + expected = { + 'configurable': false, + 'enumerable': false, + 'writable': false, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + return 'bar'; + } +}); + +tape( 'by default, the function sets a non-configurable memoized property on a provided object', function test( t ) { + var expected; + var obj; + + obj = {}; + + defineMemoizedProperty( obj, 'foo', { + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.equal( obj.foo, 'bar', 'returns expected value' ); + + expected = { + 'configurable': false, + 'enumerable': false, + 'writable': false, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + return 'bar'; + } +}); + +tape( 'the function supports setting a configurable memoized property on a provided object', function test( t ) { + var expected; + var obj; + + obj = {}; + + defineMemoizedProperty( obj, 'foo', { + 'configurable': true, + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.equal( obj.foo, 'bar', 'returns expected value' ); + + expected = { + 'configurable': true, + 'enumerable': false, + 'writable': false, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + return 'bar'; + } +}); + +tape( 'the function supports setting a non-configurable memoized property on a provided object', function test( t ) { + var expected; + var obj; + + obj = {}; + + defineMemoizedProperty( obj, 'foo', { + 'configurable': false, + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.equal( obj.foo, 'bar', 'returns expected value' ); + + expected = { + 'configurable': false, + 'enumerable': false, + 'writable': false, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + return 'bar'; + } +}); + +tape( 'until deferred evaluation, the set property is temporarily configurable', function test( t ) { + var obj; + + obj = {}; + + defineMemoizedProperty( obj, 'foo', { + 'configurable': false, + 'value': foo + }); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.equal( isConfigurableProperty( obj, 'foo' ), true, 'is configurable' ); + + t.equal( obj.foo, 'bar', 'returns expected value' ); + t.equal( isConfigurableProperty( obj, 'foo' ), false, 'is not configurable' ); + t.end(); + + function foo() { + return 'bar'; + } +}); From eb2c6e23381c1107b082864d613b1aba3b7bbf5b Mon Sep 17 00:00:00 2001 From: kgryte Date: Sun, 17 Mar 2019 00:44:16 -0700 Subject: [PATCH 090/142] Update namespace --- lib/node_modules/@stdlib/utils/lib/index.js | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/lib/node_modules/@stdlib/utils/lib/index.js b/lib/node_modules/@stdlib/utils/lib/index.js index a770b4745334..1c245863b797 100644 --- a/lib/node_modules/@stdlib/utils/lib/index.js +++ b/lib/node_modules/@stdlib/utils/lib/index.js @@ -279,6 +279,15 @@ setReadOnly( utils, 'setConfigurableReadWriteAccessor', require( '@stdlib/utils/ */ setReadOnly( utils, 'setConfigurableWriteOnlyAccessor', require( '@stdlib/utils/define-configurable-write-only-accessor' ) ); +/** +* @name defineMemoizedProperty +* @memberof utils +* @readonly +* @type {Function} +* @see {@link module:@stdlib/utils/define-memoized-property} +*/ +setReadOnly( utils, 'defineMemoizedProperty', require( '@stdlib/utils/define-memoized-property' ) ); + /** * @name setNonEnumerableProperty * @memberof utils From c840813bc3d2240f175e41ce40dde41825d88f96 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sun, 17 Mar 2019 00:46:20 -0700 Subject: [PATCH 091/142] Update namespace --- .../@stdlib/namespace/alias2pkg/data/data.csv | 1 + .../@stdlib/namespace/alias2pkg/data/data.json | 2 +- .../@stdlib/namespace/alias2related/data/data.csv | 1 + .../@stdlib/namespace/alias2related/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.txt | 1 + lib/node_modules/@stdlib/namespace/lib/namespace/d.js | 11 +++++++++++ .../@stdlib/namespace/pkg2alias/data/data.csv | 1 + .../@stdlib/namespace/pkg2alias/data/data.json | 2 +- .../@stdlib/namespace/pkg2related/data/data.csv | 1 + .../@stdlib/namespace/pkg2related/data/data.json | 2 +- lib/node_modules/@stdlib/repl/code-blocks/lib/db.js | 1 + lib/node_modules/@stdlib/repl/help/lib/db.js | 1 + 13 files changed, 23 insertions(+), 5 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index ed955b61cff6..b45c4957483c 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -852,6 +852,7 @@ deepHasOwnProp,"@stdlib/assert/deep-has-own-property" deepHasProp,"@stdlib/assert/deep-has-property" deepPluck,"@stdlib/utils/deep-pluck" deepSet,"@stdlib/utils/deep-set" +defineMemoizedProperty,"@stdlib/utils/define-memoized-property" defineProperties,"@stdlib/utils/define-properties" defineProperty,"@stdlib/utils/define-property" dirname,"@stdlib/utils/dirname" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index 155cf0e13550..f7ca9af1ab13 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ -{"AFINN_96":"@stdlib/datasets/afinn-96","AFINN_111":"@stdlib/datasets/afinn-111","alias2pkg":"@stdlib/namespace/alias2pkg","alias2related":"@stdlib/namespace/alias2related","aliases":"@stdlib/namespace/aliases","allocUnsafe":"@stdlib/buffer/alloc-unsafe","anova1":"@stdlib/stats/anova1","ANSCOMBES_QUARTET":"@stdlib/datasets/anscombes-quartet","any":"@stdlib/utils/any","anyBy":"@stdlib/utils/any-by","anyByAsync":"@stdlib/utils/async/any-by","anyByRight":"@stdlib/utils/any-by-right","anyByRightAsync":"@stdlib/utils/async/any-by-right","APERY":"@stdlib/constants/math/float64-apery","append":"@stdlib/utils/append","ARCH":"@stdlib/os/arch","argumentFunction":"@stdlib/utils/argument-function","ARGV":"@stdlib/process/argv","array":"@stdlib/ndarray/array","array2buffer":"@stdlib/buffer/from-array","array2iterator":"@stdlib/array/to-iterator","array2iteratorRight":"@stdlib/array/to-iterator-right","ArrayBuffer":"@stdlib/array/buffer","arraybuffer2buffer":"@stdlib/buffer/from-arraybuffer","arrayCtors":"@stdlib/array/ctors","arrayDataType":"@stdlib/array/dtype","arrayDataTypes":"@stdlib/array/dtypes","arrayMinDataType":"@stdlib/array/min-dtype","arrayNextDataType":"@stdlib/array/next-dtype","arrayPromotionRules":"@stdlib/array/promotion-rules","arraySafeCasts":"@stdlib/array/safe-casts","arraySameKindCasts":"@stdlib/array/same-kind-casts","arrayShape":"@stdlib/array/shape","arrayStream":"@stdlib/streams/node/from-array","arrayview2iterator":"@stdlib/array/to-view-iterator","arrayview2iteratorRight":"@stdlib/array/to-view-iterator-right","AsyncIteratorSymbol":"@stdlib/symbol/async-iterator","bartlettTest":"@stdlib/stats/bartlett-test","base.abs":"@stdlib/math/base/special/abs","base.abs2":"@stdlib/math/base/special/abs2","base.absdiff":"@stdlib/math/base/utils/absolute-difference","base.absInt32":"@stdlib/math/base/special/int32-abs","base.acos":"@stdlib/math/base/special/acos","base.acosh":"@stdlib/math/base/special/acosh","base.acoth":"@stdlib/math/base/special/acoth","base.acovercos":"@stdlib/math/base/special/acovercos","base.acoversin":"@stdlib/math/base/special/acoversin","base.ahavercos":"@stdlib/math/base/special/ahavercos","base.ahaversin":"@stdlib/math/base/special/ahaversin","base.asin":"@stdlib/math/base/special/asin","base.asinh":"@stdlib/math/base/special/asinh","base.atan":"@stdlib/math/base/special/atan","base.atan2":"@stdlib/math/base/special/atan2","base.atanh":"@stdlib/math/base/special/atanh","base.avercos":"@stdlib/math/base/special/avercos","base.aversin":"@stdlib/math/base/special/aversin","base.bernoulli":"@stdlib/math/base/special/bernoulli","base.besselj0":"@stdlib/math/base/special/besselj0","base.besselj1":"@stdlib/math/base/special/besselj1","base.bessely0":"@stdlib/math/base/special/bessely0","base.bessely1":"@stdlib/math/base/special/bessely1","base.beta":"@stdlib/math/base/special/beta","base.betainc":"@stdlib/math/base/special/betainc","base.betaincinv":"@stdlib/math/base/special/betaincinv","base.betaln":"@stdlib/math/base/special/betaln","base.binet":"@stdlib/math/base/special/binet","base.binomcoef":"@stdlib/math/base/special/binomcoef","base.binomcoefln":"@stdlib/math/base/special/binomcoefln","base.boxcox":"@stdlib/math/base/special/boxcox","base.boxcox1p":"@stdlib/math/base/special/boxcox1p","base.boxcox1pinv":"@stdlib/math/base/special/boxcox1pinv","base.boxcoxinv":"@stdlib/math/base/special/boxcoxinv","base.cabs":"@stdlib/math/base/complex/abs","base.cabs2":"@stdlib/math/base/complex/abs2","base.cadd":"@stdlib/math/base/complex/add","base.cbrt":"@stdlib/math/base/special/cbrt","base.cceil":"@stdlib/math/base/complex/ceil","base.cceiln":"@stdlib/math/base/complex/ceiln","base.ccis":"@stdlib/math/base/complex/cis","base.cdiv":"@stdlib/math/base/complex/divide","base.ceil":"@stdlib/math/base/special/ceil","base.ceil2":"@stdlib/math/base/special/ceil2","base.ceil10":"@stdlib/math/base/special/ceil10","base.ceilb":"@stdlib/math/base/special/ceilb","base.ceiln":"@stdlib/math/base/special/ceiln","base.ceilsd":"@stdlib/math/base/special/ceilsd","base.cexp":"@stdlib/math/base/complex/exp","base.cflipsign":"@stdlib/math/base/complex/flipsign","base.cfloor":"@stdlib/math/base/complex/floor","base.cfloorn":"@stdlib/math/base/complex/floorn","base.cinv":"@stdlib/math/base/complex/inv","base.clamp":"@stdlib/math/base/special/clamp","base.cmul":"@stdlib/math/base/complex/multiply","base.cneg":"@stdlib/math/base/complex/negate","base.continuedFraction":"@stdlib/math/base/tools/continued-fraction","base.copysign":"@stdlib/math/base/special/copysign","base.cos":"@stdlib/math/base/special/cos","base.cosh":"@stdlib/math/base/special/cosh","base.cosm1":"@stdlib/math/base/special/cosm1","base.cospi":"@stdlib/math/base/special/cospi","base.covercos":"@stdlib/math/base/special/covercos","base.coversin":"@stdlib/math/base/special/coversin","base.cphase":"@stdlib/math/base/complex/phase","base.cpolar":"@stdlib/math/base/complex/polar","base.cround":"@stdlib/math/base/complex/round","base.croundn":"@stdli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ib/regexp/dirname","RE_DIRNAME_POSIX":"@stdlib/regexp/dirname-posix","RE_DIRNAME_WINDOWS":"@stdlib/regexp/dirname-windows","RE_EOL":"@stdlib/regexp/eol","RE_EXTENDED_LENGTH_PATH":"@stdlib/regexp/extended-length-path","RE_EXTNAME":"@stdlib/regexp/extname","RE_EXTNAME_POSIX":"@stdlib/regexp/extname-posix","RE_EXTNAME_WINDOWS":"@stdlib/regexp/extname-windows","RE_FILENAME":"@stdlib/regexp/filename","RE_FILENAME_POSIX":"@stdlib/regexp/filename-posix","RE_FILENAME_WINDOWS":"@stdlib/regexp/filename-windows","RE_FUNCTION_NAME":"@stdlib/regexp/function-name","RE_NATIVE_FUNCTION":"@stdlib/regexp/native-function","RE_REGEXP":"@stdlib/regexp/regexp","RE_UNC_PATH":"@stdlib/regexp/unc-path","RE_UTF16_SURROGATE_PAIR":"@stdlib/regexp/utf16-surrogate-pair","RE_UTF16_UNPAIRED_SURROGATE":"@stdlib/regexp/utf16-unpaired-surrogate","RE_WHITESPACE":"@stdlib/regexp/whitespace","readDir":"@stdlib/fs/read-dir","readFile":"@stdlib/fs/read-file","readFileList":"@stdlib/fs/read-file-list","readJSON":"@stdlib/fs/read-json","readWASM":"@stdlib/fs/read-wasm","real":"@stdlib/complex/real","realmax":"@stdlib/utils/real-max","realmin":"@stdlib/utils/real-min","reduce":"@stdlib/utils/reduce","reduceAsync":"@stdlib/utils/async/reduce","reduceRight":"@stdlib/utils/reduce-right","reduceRightAsync":"@stdlib/utils/async/reduce-right","reFromString":"@stdlib/utils/regexp-from-string","reim":"@stdlib/complex/reim","removeFirst":"@stdlib/string/remove-first","removeLast":"@stdlib/string/remove-last","removePunctuation":"@stdlib/string/remove-punctuation","removeUTF8BOM":"@stdlib/string/remove-utf8-bom","removeWords":"@stdlib/string/remove-words","rename":"@stdlib/fs/rename","reorderArguments":"@stdlib/utils/reorder-arguments","repeat":"@stdlib/string/repeat","replace":"@stdlib/string/replace","rescape":"@stdlib/utils/escape-regexp-string","resolveParentPath":"@stdlib/fs/resolve-parent-path","reverseArguments":"@stdlib/utils/reverse-arguments","reverseString":"@stdlib/string/reverse","reviveBasePRNG":"@stdlib/random/base/reviver","reviveBuffer":"@stdlib/buffer/reviver","reviveComplex":"@stdlib/complex/reviver","reviveComplex64":"@stdlib/complex/reviver-float32","reviveComplex128":"@stdlib/complex/reviver-float64","reviveError":"@stdlib/error/reviver","reviveTypedArray":"@stdlib/array/reviver","rpad":"@stdlib/string/right-pad","rtrim":"@stdlib/string/right-trim","safeintmax":"@stdlib/utils/safe-int-max","safeintmin":"@stdlib/utils/safe-int-min","sample":"@stdlib/random/sample","SAVOY_STOPWORDS_FIN":"@stdlib/datasets/savoy-stopwords-fin","SAVOY_STOPWORDS_FR":"@stdlib/datasets/savoy-stopwords-fr","SAVOY_STOPWORDS_GER":"@stdlib/datasets/savoy-stopwords-ger","SAVOY_STOPWORDS_IT":"@stdlib/datasets/savoy-stopwords-it","SAVOY_STOPWORDS_POR":"@stdlib/datasets/savoy-stopwords-por","SAVOY_STOPWORDS_SP":"@stdlib/datasets/savoy-stopwords-sp","SAVOY_STOPWORDS_SWE":"@stdlib/datasets/savoy-stopwords-swe","SECONDS_IN_DAY":"@stdlib/constants/time/seconds-in-day","SECONDS_IN_HOUR":"@stdlib/constants/time/seconds-in-hour","SECONDS_IN_MINUTE":"@stdlib/constants/time/seconds-in-minute","SECONDS_IN_WEEK":"@stdlib/constants/time/seconds-in-week","secondsInMonth":"@stdlib/time/seconds-in-month","secondsInYear":"@stdlib/time/seconds-in-year","setConfigurableReadOnly":"@stdlib/utils/define-configurable-read-only-property","setConfigurableReadOnlyAccessor":"@stdlib/utils/define-configurable-read-only-accessor","setConfigurableReadWriteAccessor":"@stdlib/utils/define-configurable-read-write-accessor","setConfigurableWriteOnlyAccessor":"@stdlib/utils/define-configurable-write-only-accessor","setNonEnumerableProperty":"@stdlib/utils/define-nonenumerable-property","setNonEnumerableReadOnly":"@stdlib/utils/define-nonenumerable-read-only-property","setNonEnumerableReadOnlyAccessor":"@stdlib/utils/define-nonenumerable-read-only-accessor","setNonEnumerableReadWriteAccessor":"@stdlib/utils/define-nonenumerable-read-write-accessor","setNonEnumerableWriteOnlyAccessor":"@stdlib/utils/define-nonenumerable-write-only-accessor","setReadOnly":"@stdlib/utils/define-read-only-property","setReadOnlyAccessor":"@stdlib/utils/define-read-only-accessor","setReadWriteAccessor":"@stdlib/utils/define-read-write-accessor","setWriteOnlyAccessor":"@stdlib/utils/define-write-only-accessor","SharedArrayBuffer":"@stdlib/array/shared-buffer","shift":"@stdlib/utils/shift","shuffle":"@stdlib/random/shuffle","sizeOf":"@stdlib/utils/size-of","some":"@stdlib/utils/some","someBy":"@stdlib/utils/some-by","someByAsync":"@stdlib/utils/async/some-by","someByRight":"@stdlib/utils/some-by-right","someByRightAsync":"@stdlib/utils/async/some-by-right","SOTU":"@stdlib/datasets/sotu","SPACHE_REVISED":"@stdlib/datasets/spache-revised","SPAM_ASSASSIN":"@stdlib/datasets/spam-assassin","SparklineBase":"@stdlib/plot/sparklines/base/ctor","sparsearray2iterator":"@stdlib/array/to-sparse-iterator","sparsearray2iteratorRight":"@stdlib/array/to-sparse-iterator-right","splitStream":"@stdlib/streams/node/split","SQRT_EPS":"@stdlib/consta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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv index 1cab98b0c5aa..99a93407e367 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv @@ -852,6 +852,7 @@ deepHasOwnProp,"deepHasProp,hasOwnProp,deepGet,deepPluck,deepSet" deepHasProp,"deepHasOwnProp,hasOwnProp,deepGet,deepPluck,deepSet" deepPluck,"deepGet,deepSet" deepSet,"deepGet,deepPluck" +defineMemoizedProperty,"defineProperty" defineProperties,"defineProperty,setReadOnly" defineProperty,"defineProperties,setReadOnly" dirname,"extname" diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.json b/lib/node_modules/@stdlib/namespace/alias2related/data/data.json index 0f1fee3da9fa..99ecd84dc1e1 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index 5699f2a9c9a1..a5d1c15a7945 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -852,6 +852,7 @@ deepHasOwnProp deepHasProp deepPluck deepSet +defineMemoizedProperty defineProperties defineProperty dirname diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/d.js b/lib/node_modules/@stdlib/namespace/lib/namespace/d.js index 97edc0ff06bd..383cbc61ae46 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/d.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/d.js @@ -174,6 +174,17 @@ ns.push({ ] }); +ns.push({ + 'alias': 'defineMemoizedProperty', + 'path': '@stdlib/utils/define-memoized-property', + 'value': require( '@stdlib/utils/define-memoized-property' ), + 'type': 'Function', + 'related': [ + '@stdlib/utils/define-memoized-read-only-property', + '@stdlib/utils/define-property' + ] +}); + ns.push({ 'alias': 'defineProperties', 'path': '@stdlib/utils/define-properties', diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index 9335fd88132a..470bbca12ab0 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -852,6 +852,7 @@ "@stdlib/assert/deep-has-property",deepHasProp "@stdlib/utils/deep-pluck",deepPluck "@stdlib/utils/deep-set",deepSet +"@stdlib/utils/define-memoized-property",defineMemoizedProperty "@stdlib/utils/define-properties",defineProperties "@stdlib/utils/define-property",defineProperty "@stdlib/utils/dirname",dirname diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index 4ae61e34b986..6d7ba140cd5c 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ 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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv index dbda789352c7..d89becfbd8d1 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv @@ -852,6 +852,7 @@ "@stdlib/assert/deep-has-property","@stdlib/assert/deep-has-own-property,@stdlib/assert/has-own-property,@stdlib/utils/deep-get,@stdlib/utils/deep-pluck,@stdlib/utils/deep-set" "@stdlib/utils/deep-pluck","@stdlib/utils/deep-get,@stdlib/utils/deep-set" "@stdlib/utils/deep-set","@stdlib/utils/deep-get,@stdlib/utils/deep-pluck" +"@stdlib/utils/define-memoized-property","@stdlib/utils/define-property" "@stdlib/utils/define-properties","@stdlib/utils/define-property,@stdlib/utils/define-read-only-property" "@stdlib/utils/define-property","@stdlib/utils/define-properties,@stdlib/utils/define-read-only-property" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index dbb736ddd50a..3fa516430272 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -873,6 +873,7 @@ var db = { "deepHasProp": "function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nobj = { 'a': new Foo() };\nbool = deepHasProp( obj, 'a.b.c' )\n\n// Specify a custom separator via the `sep` option:\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n", "deepPluck": "arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n];\nout = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n];\nout = deepPluck( arr, [ 'a', 1 ] )\n", "deepSet": "obj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a.b.c', 'beep' )\n\n// Specify an alternative separator via the sep option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\n\n// To create a key path which does not exist, set the create option to true:\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n", + "defineMemoizedProperty": "obj = {};\nfunction foo() {\n return 'bar';\n};\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n});\nobj.foo\n", "defineProperties": "obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n});\nobj.foo\nobj.baz\n", "defineProperty": "obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n});\nobj.foo = 'boop';\nobj\n", "dirname": "dir = dirname( './foo/bar/index.js' )\n", diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index 05cafc424d68..109bdec9d625 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -873,6 +873,7 @@ var db = { "deepHasProp": "\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n", "deepPluck": "\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n", "deepSet": "\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n", + "defineMemoizedProperty": "\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineProperty\n", "defineProperties": "\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n", "defineProperty": "\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n", "dirname": "\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n", From 7ecde2e960c8dd9980bc363a30054abd7835dde8 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sun, 17 Mar 2019 01:42:38 -0700 Subject: [PATCH 092/142] Add utility to define a memoized read-only property --- .../README.md | 110 ++++++++++++++ .../benchmark/benchmark.js | 58 +++++++ .../docs/repl.txt | 29 ++++ .../docs/types/index.d.ts | 60 ++++++++ .../docs/types/test.ts | 57 +++++++ .../examples/index.js | 45 ++++++ .../lib/index.js | 48 ++++++ .../lib/main.js | 73 +++++++++ .../package.json | 76 ++++++++++ .../test/test.js | 142 ++++++++++++++++++ 10 files changed, 698 insertions(+) create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-read-only-property/README.md create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-read-only-property/benchmark/benchmark.js create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-read-only-property/examples/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-read-only-property/lib/index.js create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-read-only-property/lib/main.js create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-read-only-property/package.json create mode 100644 lib/node_modules/@stdlib/utils/define-memoized-read-only-property/test/test.js diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/README.md b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/README.md new file mode 100644 index 000000000000..ced87c79c5f2 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/README.md @@ -0,0 +1,110 @@ + + +# Memoized Read-Only + +> [Define][mdn-define-property] a memoized **read-only** object property. + +
+ +## Usage + +```javascript +var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); +``` + +#### setMemoizedReadOnly( obj, prop, fcn ) + +[Defines][mdn-define-property] a memoized **read-only** object property. + +```javascript +var obj = {}; + +function foo() { + return 'bar'; +} + +setMemoizedReadOnly( obj, 'foo', foo ); + +var v = obj.foo; +// returns 'bar' +``` + +The last argument should be a synchronous function whose return value will be memoized and set as the property value. + +
+ + + +
+ +## Notes + +- A **read-only** property is **enumerable** and **non-configurable**; however, until deferred evaluation, an object property is **configurable**. + +
+ + + +
+ +## Examples + + + +```javascript +var fibonacci = require( '@stdlib/math/base/special/fibonacci' ); +var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); + +function Foo() { + var self; + if ( !(this instanceof Foo) ) { + return new Foo(); + } + self = this; + this.count = 0; + setMemoizedReadOnly( this, 'fibo', fibo ); + return this; + + function fibo() { + self.count += 1; + return fibonacci( 73 ); + } +} + +var foo = new Foo(); + +var i; +for ( i = 0; i < 10; i++ ) { + console.log( 'F: %d. Count: %d.', foo.fibo, foo.count ); +} +``` + +
+ + + +
+ +[mdn-define-property]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Object/defineProperty + +
+ + diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/benchmark/benchmark.js b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/benchmark/benchmark.js new file mode 100644 index 000000000000..ecc5cedf2db7 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/benchmark/benchmark.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var fromCodePoint = require( '@stdlib/string/from-code-point' ); +var pkg = require( './../package.json' ).name; +var setMemoizedReadOnly = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var obj; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + obj = {}; + setMemoizedReadOnly( obj, 'foo', f( i ) ); + if ( !isString( obj.foo ) ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( obj.foo ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); + + function f( i ) { + return fcn; + + function fcn() { + return fromCodePoint( 97 + (i%26) ); + } + } +}); diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/repl.txt b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/repl.txt new file mode 100644 index 000000000000..47312433e1b3 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/repl.txt @@ -0,0 +1,29 @@ + +{{alias}}( obj, prop, fcn ) + Defines a memoized read-only object property. + + Read-only properties are enumerable and non-configurable. + + Parameters + ---------- + obj: Object + Object on which to define the property. + + prop: string|symbol + Property name. + + fcn: Function + Synchronous function whose return value will be memoized and set as the + property value. + + Examples + -------- + > var obj = {}; + > function foo() { return 'bar'; }; + > {{alias}}( obj, 'foo', foo ); + > obj.foo + 'bar' + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/types/index.d.ts b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/types/index.d.ts new file mode 100644 index 000000000000..782db378ce27 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/types/index.d.ts @@ -0,0 +1,60 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/// + +import { PropertyName } from '@stdlib/types/object'; + +/** +* Returns a property value. +* +* @returns property value +*/ +type Getter = () => any; + +/** +* Defines a memoized read-only object property. +* +* ## Notes +* +* - Read-only properties are **enumerable** and **non-configurable**. +* +* @param obj - object on which to define property +* @param prop - property name +* @param fcn - function whose return value will be memoized and set as the property value +* +* @example +* var obj = {}; +* +* function foo() { +* return 'bar'; +* } +* +* setMemoizedReadOnly( obj, 'foo', foo ); +* +* var v = obj.foo; +* // returns 'bar' +*/ +declare function setMemoizedReadOnly( obj: any, prop: PropertyName, fcn: Getter ): void; // tslint:disable-line: max-line-length + + +// EXPORTS // + +export = setMemoizedReadOnly; diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/types/test.ts b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/types/test.ts new file mode 100644 index 000000000000..03a072d8ca4d --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/docs/types/test.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import setMemoizedReadOnly = require( './index' ); + + +// TESTS // + +// The function returns `undefined`... +{ + setMemoizedReadOnly( {}, 'foo', (): string => 'bar' ); // $ExpectType void +} + +// The compiler throws an error if the function is provided a second argument which is not a valid property name... +{ + setMemoizedReadOnly( {}, true, (): string => 'bar' ); // $ExpectError + setMemoizedReadOnly( {}, false, (): string => 'bar' ); // $ExpectError + setMemoizedReadOnly( {}, null, (): string => 'bar' ); // $ExpectError + setMemoizedReadOnly( {}, undefined, (): string => 'bar' ); // $ExpectError + setMemoizedReadOnly( {}, [], (): string => 'bar' ); // $ExpectError + setMemoizedReadOnly( {}, {}, (): string => 'bar' ); // $ExpectError + setMemoizedReadOnly( {}, ( x: number ): number => x, (): string => 'bar' ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a getter... +{ + setMemoizedReadOnly( {}, 'foo', '5' ); // $ExpectError + setMemoizedReadOnly( {}, 'foo', 5 ); // $ExpectError + setMemoizedReadOnly( {}, 'foo', true ); // $ExpectError + setMemoizedReadOnly( {}, 'foo', false ); // $ExpectError + setMemoizedReadOnly( {}, 'foo', null ); // $ExpectError + setMemoizedReadOnly( {}, 'foo', undefined ); // $ExpectError + setMemoizedReadOnly( {}, 'foo', [] ); // $ExpectError + setMemoizedReadOnly( {}, 'foo', {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + setMemoizedReadOnly(); // $ExpectError + setMemoizedReadOnly( {} ); // $ExpectError + setMemoizedReadOnly( {}, 'foo' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/examples/index.js b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/examples/index.js new file mode 100644 index 000000000000..51b218866927 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var fibonacci = require( '@stdlib/math/base/special/fibonacci' ); +var setMemoizedReadOnly = require( './../lib' ); + +function Foo() { + var self; + if ( !(this instanceof Foo) ) { + return new Foo(); + } + self = this; + setMemoizedReadOnly( this, 'fibo', fibo ); + this.count = 0; + return this; + + function fibo() { + self.count += 1; + return fibonacci( 73 ); + } +} + +var foo = new Foo(); + +var i; +for ( i = 0; i < 10; i++ ) { + console.log( 'F: %d. Count: %d.', foo.fibo, foo.count ); +} diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/lib/index.js b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/lib/index.js new file mode 100644 index 000000000000..faf887e85876 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/lib/index.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Define a memoized read-only object property. +* +* @module @stdlib/utils/define-memoized-read-only-property +* +* @example +* var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); +* +* var obj = {}; +* +* function foo() { +* return 'bar'; +* } +* +* setMemoizedReadOnly( obj, 'foo', foo ); +* +* var v = obj.foo; +* // returns 'bar' +*/ + +// MODULES // + +var setMemoizedReadOnly = require( './main.js' ); + + +// EXPORTS // + +module.exports = setMemoizedReadOnly; diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/lib/main.js b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/lib/main.js new file mode 100644 index 000000000000..9c16f9fc3d5b --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/lib/main.js @@ -0,0 +1,73 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isObject = require( '@stdlib/assert/is-object' ); +var isFunction = require( '@stdlib/assert/is-function' ); +var defineMemoizedProperty = require( '@stdlib/utils/define-memoized-property' ); + + +// MAIN // + +/** +* Defines a memoized read-only object property. +* +* ## Notes +* +* - Read-only properties are **enumerable** and **non-configurable**. +* +* @param {Object} obj - object on which to define the property +* @param {(string|symbol)} prop - property name +* @param {Function} fcn - function whose return value will be memoized and set as the property value +* @throws {TypeError} first argument must be an object +* @throws {TypeError} third argument must be a function +* +* @example +* var obj = {}; +* +* function foo() { +* return 'bar'; +* } +* +* setMemoizedReadOnly( obj, 'foo', foo ); +* +* var v = obj.foo; +* // returns 'bar' +*/ +function setMemoizedReadOnly( obj, prop, fcn ) { + if ( !isObject( obj ) ) { + throw new TypeError( 'invalid argument. First argument must be an object. Value: `' + obj + '`.' ); + } + if ( !isFunction( fcn ) ) { + throw new TypeError( 'invalid argument. Third argument must be a function. Value: `' + fcn + '`.' ); + } + defineMemoizedProperty( obj, prop, { + 'configurable': false, + 'enumerable': true, + 'writable': false, + 'value': fcn + }); +} + + +// EXPORTS // + +module.exports = setMemoizedReadOnly; diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/package.json b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/package.json new file mode 100644 index 000000000000..d70aeef2bef3 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/utils/define-memoized-read-only-property", + "version": "0.0.0", + "description": "Define a memoized read-only object property.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdutils", + "stdutil", + "utilities", + "utility", + "utils", + "util", + "object", + "property", + "define", + "set", + "value", + "prop", + "descriptor", + "writable", + "read-only", + "configurable", + "enumerable", + "memoized", + "memoize", + "deferred", + "defer", + "lazy" + ] +} diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/test/test.js b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/test/test.js new file mode 100644 index 000000000000..f8138c8af903 --- /dev/null +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/test/test.js @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var noop = require( '@stdlib/utils/noop' ); +var isEnumerableProperty = require( '@stdlib/assert/is-enumerable-property' ); +var isWritableProperty = require( '@stdlib/assert/is-writable-property' ); +var isConfigurableProperty = require( '@stdlib/assert/is-configurable-property' ); +var propertyDescriptor = require( '@stdlib/utils/property-descriptor' ); +var setMemoizedReadOnly = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.equal( typeof setMemoizedReadOnly, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not an object', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0 + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + setMemoizedReadOnly( value, 'foo', noop ); + }; + } +}); + +tape( 'the function throws an error if provided a third argument which is not a function', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + setMemoizedReadOnly( {}, 'foo', value ); + }; + } +}); + +tape( 'the function sets a memoized read-only property on a provided object', function test( t ) { + var expected; + var count; + var obj; + var i; + + obj = {}; + count = 0; + + setMemoizedReadOnly( obj, 'foo', foo ); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + for ( i = 0; i < 10; i++ ) { + t.equal( obj.foo, 'bar', 'returns expected value' ); + t.equal( count, 1, 'returns expected value' ); + } + expected = { + 'configurable': false, + 'enumerable': true, + 'writable': false, + 'value': 'bar' + }; + t.deepEqual( propertyDescriptor( obj, 'foo' ), expected, 'has expected descriptor' ); + t.end(); + + function foo() { + count += 1; + return 'bar'; + } +}); + +tape( 'until deferred evaluation, the set property is temporarily configurable', function test( t ) { + var obj; + + obj = {}; + setMemoizedReadOnly( obj, 'foo', foo ); + t.equal( hasOwnProp( obj, 'foo' ), true, 'has property' ); + t.equal( isEnumerableProperty( obj, 'foo' ), true, 'is enumerable' ); + t.equal( isWritableProperty( obj, 'foo' ), false, 'is not writable' ); + t.equal( isConfigurableProperty( obj, 'foo' ), true, 'is configurable' ); + + t.equal( obj.foo, 'bar', 'returns expected value' ); + t.equal( isEnumerableProperty( obj, 'foo' ), true, 'is enumerable' ); + t.equal( isWritableProperty( obj, 'foo' ), false, 'is not writable' ); + t.equal( isConfigurableProperty( obj, 'foo' ), false, 'is not configurable' ); + t.end(); + + function foo() { + return 'bar'; + } +}); From 5cb605d4a41e34fee83ac64df096fb4e8593e8e3 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sun, 17 Mar 2019 01:44:36 -0700 Subject: [PATCH 093/142] Update namespace --- lib/node_modules/@stdlib/utils/lib/index.js | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/lib/node_modules/@stdlib/utils/lib/index.js b/lib/node_modules/@stdlib/utils/lib/index.js index 1c245863b797..52c2968069a0 100644 --- a/lib/node_modules/@stdlib/utils/lib/index.js +++ b/lib/node_modules/@stdlib/utils/lib/index.js @@ -288,6 +288,15 @@ setReadOnly( utils, 'setConfigurableWriteOnlyAccessor', require( '@stdlib/utils/ */ setReadOnly( utils, 'defineMemoizedProperty', require( '@stdlib/utils/define-memoized-property' ) ); +/** +* @name setMemoizedReadOnly +* @memberof utils +* @readonly +* @type {Function} +* @see {@link module:@stdlib/utils/define-memoized-read-only-property} +*/ +setReadOnly( utils, 'setMemoizedReadOnly', require( '@stdlib/utils/define-memoized-read-only-property' ) ); + /** * @name setNonEnumerableProperty * @memberof utils From ad868c8d967638c8ae57134e27ae8de5a19cdaa9 Mon Sep 17 00:00:00 2001 From: kgryte Date: Sun, 17 Mar 2019 01:45:22 -0700 Subject: [PATCH 094/142] Update namespace --- .../@stdlib/namespace/alias2pkg/data/data.csv | 1 + .../@stdlib/namespace/alias2pkg/data/data.json | 2 +- .../@stdlib/namespace/alias2related/data/data.csv | 3 ++- .../@stdlib/namespace/alias2related/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.json | 2 +- .../@stdlib/namespace/aliases/data/data.txt | 1 + lib/node_modules/@stdlib/namespace/lib/namespace/s.js | 11 +++++++++++ .../@stdlib/namespace/pkg2alias/data/data.csv | 1 + .../@stdlib/namespace/pkg2alias/data/data.json | 2 +- .../@stdlib/namespace/pkg2related/data/data.csv | 3 ++- .../@stdlib/namespace/pkg2related/data/data.json | 2 +- lib/node_modules/@stdlib/repl/code-blocks/lib/db.js | 1 + lib/node_modules/@stdlib/repl/help/lib/db.js | 3 ++- 13 files changed, 26 insertions(+), 8 deletions(-) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index b45c4957483c..bed1410ced5d 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1764,6 +1764,7 @@ setConfigurableReadOnly,"@stdlib/utils/define-configurable-read-only-property" setConfigurableReadOnlyAccessor,"@stdlib/utils/define-configurable-read-only-accessor" setConfigurableReadWriteAccessor,"@stdlib/utils/define-configurable-read-write-accessor" setConfigurableWriteOnlyAccessor,"@stdlib/utils/define-configurable-write-only-accessor" +setMemoizedReadOnly,"@stdlib/utils/define-memoized-read-only-property" setNonEnumerableProperty,"@stdlib/utils/define-nonenumerable-property" setNonEnumerableReadOnly,"@stdlib/utils/define-nonenumerable-read-only-property" setNonEnumerableReadOnlyAccessor,"@stdlib/utils/define-nonenumerable-read-only-accessor" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index f7ca9af1ab13..6e619cfb570e 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ -{"AFINN_96":"@stdlib/datasets/afinn-96","AFINN_111":"@stdlib/datasets/afinn-111","alias2pkg":"@stdlib/namespace/alias2pkg","alias2related":"@stdlib/namespace/alias2related","aliases":"@stdlib/namespace/aliases","allocUnsafe":"@stdlib/buffer/alloc-unsafe","anova1":"@stdlib/stats/anova1","ANSCOMBES_QUARTET":"@stdlib/datasets/anscombes-quartet","any":"@stdlib/utils/any","anyBy":"@stdlib/utils/any-by","anyByAsync":"@stdlib/utils/async/any-by","anyByRight":"@stdlib/utils/any-by-right","anyByRightAsync":"@stdlib/utils/async/any-by-right","APERY":"@stdlib/constants/math/float64-apery","append":"@stdlib/utils/append","ARCH":"@stdlib/os/arch","argumentFunction":"@stdlib/utils/argument-function","ARGV":"@stdlib/process/argv","array":"@stdlib/ndarray/array","array2buffer":"@stdlib/buffer/from-array","array2iterator":"@stdlib/array/to-iterator","array2iteratorRight":"@stdlib/array/to-iterator-right","ArrayBuffer":"@stdlib/array/buffer","arraybuffer2buffer":"@stdlib/buffer/from-arraybuffer","arrayCtors":"@stdlib/array/ctors","arrayDataType":"@stdlib/array/dtype","arrayDataTypes":"@stdlib/array/dtypes","arrayMinDataType":"@stdlib/array/min-dtype","arrayNextDataType":"@stdlib/array/next-dtype","arrayPromotionRules":"@stdlib/array/promotion-rules","arraySafeCasts":"@stdlib/array/safe-casts","arraySameKindCasts":"@stdlib/array/same-kind-casts","arrayShape":"@stdlib/array/shape","arrayStream":"@stdlib/streams/node/from-array","arrayview2iterator":"@stdlib/array/to-view-iterator","arrayview2iteratorRight":"@stdlib/array/to-view-iterator-right","AsyncIteratorSymbol":"@stdlib/symbol/async-iterator","bartlettTest":"@stdlib/stats/bartlett-test","base.abs":"@stdlib/math/base/special/abs","base.abs2":"@stdlib/math/base/special/abs2","base.absdiff":"@stdlib/math/base/utils/absolute-difference","base.absInt32":"@stdlib/math/base/special/int32-abs","base.acos":"@stdlib/math/base/special/acos","base.acosh":"@stdlib/math/base/special/acosh","base.acoth":"@stdlib/math/base/special/acoth","base.acovercos":"@stdlib/math/base/special/acovercos","base.acoversin":"@stdlib/math/base/special/acoversin","base.ahavercos":"@stdlib/math/base/special/ahavercos","base.ahaversin":"@stdlib/math/base/special/ahaversin","base.asin":"@stdlib/math/base/special/asin","base.asinh":"@stdlib/math/base/special/asinh","base.atan":"@stdlib/math/base/special/atan","base.atan2":"@stdlib/math/base/special/atan2","base.atanh":"@stdlib/math/base/special/atanh","base.avercos":"@stdlib/math/base/special/avercos","base.aversin":"@stdlib/math/base/special/aversin","base.bernoulli":"@stdlib/math/base/special/bernoulli","base.besselj0":"@stdlib/math/base/special/besselj0","base.besselj1":"@stdlib/math/base/special/besselj1","base.bessely0":"@stdlib/math/base/special/bessely0","base.bessely1":"@stdlib/math/base/special/bessely1","base.beta":"@stdlib/math/base/special/beta","base.betainc":"@stdlib/math/base/special/betainc","base.betaincinv":"@stdlib/math/base/special/betaincinv","base.betaln":"@stdlib/math/base/special/betaln","base.binet":"@stdlib/math/base/special/binet","base.binomcoef":"@stdlib/math/base/special/binomcoef","base.binomcoefln":"@stdlib/math/base/special/binomcoefln","base.boxcox":"@stdlib/math/base/special/boxcox","base.boxcox1p":"@stdlib/math/base/special/boxcox1p","base.boxcox1pinv":"@stdlib/math/base/special/boxcox1pinv","base.boxcoxinv":"@stdlib/math/base/special/boxcoxinv","base.cabs":"@stdlib/math/base/complex/abs","base.cabs2":"@stdlib/math/base/complex/abs2","base.cadd":"@stdlib/math/base/complex/add","base.cbrt":"@stdlib/math/base/special/cbrt","base.cceil":"@stdlib/math/base/complex/ceil","base.cceiln":"@stdlib/math/base/complex/ceiln","base.ccis":"@stdlib/math/base/complex/cis","base.cdiv":"@stdlib/math/base/complex/divide","base.ceil":"@stdlib/math/base/special/ceil","base.ceil2":"@stdlib/math/base/special/ceil2","base.ceil10":"@stdlib/math/base/special/ceil10","base.ceilb":"@stdlib/math/base/special/ceilb","base.ceiln":"@stdlib/math/base/special/ceiln","base.ceilsd":"@stdlib/math/base/special/ceilsd","base.cexp":"@stdlib/math/base/complex/exp","base.cflipsign":"@stdlib/math/base/complex/flipsign","base.cfloor":"@stdlib/math/base/complex/floor","base.cfloorn":"@stdlib/math/base/complex/floorn","base.cinv":"@stdlib/math/base/complex/inv","base.clamp":"@stdlib/math/base/special/clamp","base.cmul":"@stdlib/math/base/complex/multiply","base.cneg":"@stdlib/math/base/complex/negate","base.continuedFraction":"@stdlib/math/base/tools/continued-fraction","base.copysign":"@stdlib/math/base/special/copysign","base.cos":"@stdlib/math/base/special/cos","base.cosh":"@stdlib/math/base/special/cosh","base.cosm1":"@stdlib/math/base/special/cosm1","base.cospi":"@stdlib/math/base/special/cospi","base.covercos":"@stdlib/math/base/special/covercos","base.coversin":"@stdlib/math/base/special/coversin","base.cphase":"@stdlib/math/base/complex/phase","base.cpolar":"@stdlib/math/base/complex/polar","base.cround":"@stdlib/math/base/complex/round","base.croundn":"@stdli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araswamy/variance","base.dists.laplace.cdf":"@stdlib/stats/base/dists/laplace/cdf","base.dists.laplace.entropy":"@stdlib/stats/base/dists/laplace/entropy","base.dists.laplace.kurtosis":"@stdlib/stats/base/dists/laplace/kurtosis","base.dists.laplace.Laplace":"@stdlib/stats/base/dists/laplace/ctor","base.dists.laplace.logcdf":"@stdlib/stats/base/dists/laplace/logcdf","base.dists.laplace.logpdf":"@stdlib/stats/base/dists/laplace/logpdf","base.dists.laplace.mean":"@stdlib/stats/base/dists/laplace/mean","base.dists.laplace.median":"@stdlib/stats/base/dists/laplace/median","base.dists.laplace.mgf":"@stdlib/stats/base/dists/laplace/mgf","base.dists.laplace.mode":"@stdlib/stats/base/dists/laplace/mode","base.dists.laplace.pdf":"@stdlib/stats/base/dists/laplace/pdf","base.dists.laplace.quantile":"@stdlib/stats/base/dists/laplace/quantile","base.dists.laplace.skewness":"@stdlib/stats/base/dists/laplace/skewness","base.dists.laplace.stdev":"@stdlib/stats/base/dists/laplace/stdev","base.dists.laplace.variance":"@stdlib/stats/base/dists/laplace/variance","base.dists.levy.cdf":"@stdlib/stats/base/dists/levy/cdf","base.dists.levy.entropy":"@stdlib/stats/base/dists/levy/entropy","base.dists.levy.Levy":"@stdlib/stats/base/dists/levy/ctor","base.dists.levy.logcdf":"@stdlib/stats/base/dists/levy/logcdf","base.dists.levy.logpdf":"@stdlib/stats/base/dists/levy/logpdf","base.dists.levy.mean":"@stdlib/stats/base/dists/levy/mean","base.dists.levy.median":"@stdlib/stats/base/dists/levy/median","base.dists.levy.mode":"@stdlib/stats/base/dists/levy/mode","base.dists.levy.pdf":"@stdlib/stats/base/dists/levy/pdf","base.dists.levy.quantile":"@stdlib/stats/base/dists/levy/quantile","base.dists.levy.stdev":"@stdlib/stats/base/dists/levy/stdev","base.dists.levy.variance":"@stdlib/stats/base/dists/levy/variance","base.dists.logistic.cdf":"@stdlib/stats/base/dists/logistic/cdf","base.dists.logistic.entropy":"@stdlib/stats/base/dists/logistic/entropy","base.dists.logistic.kurtosis":"@stdlib/stats/base/dists/logistic/kurtosis","base.dists.logistic.logcdf":"@stdlib/stats/base/dists/logistic/logcdf","base.dists.logistic.Logistic":"@stdlib/stats/base/dists/logistic/ctor","base.dists.logistic.logpdf":"@stdlib/stats/base/dists/logistic/logpdf","base.dists.logistic.mean":"@stdlib/stats/base/dists/logistic/mean","base.dists.logistic.median":"@stdlib/stats/base/dists/logistic/median","base.dists.logistic.mgf":"@stdlib/stats/base/dists/logistic/mgf","base.dists.logistic.mode":"@stdlib/stats/base/dists/logistic/mode","base.dists.logistic.pdf":"@stdlib/stats/base/dists/logistic/pdf","base.dists.logistic.quantile":"@stdlib/stats/base/dists/logistic/quantile","base.dists.logistic.skewness":"@stdlib/stats/base/dists/logistic/skewness","base.dists.logistic.stdev":"@stdlib/stats/base/dists/logistic/stdev","base.dists.logistic.variance":"@stdlib/stats/base/dists/logistic/variance","base.dists.lognormal.cdf":"@stdlib/stats/base/dists/lognormal/cdf","base.dists.lognormal.entropy":"@stdlib/stats/base/dists/lognormal/entropy","base.dists.lognormal.kurtosis":"@stdlib/stats/base/dists/lognormal/kurtosis","base.dists.lognormal.LogNormal":"@stdlib/stats/base/dists/lognormal/ctor","base.dists.lognormal.logpdf":"@stdlib/stats/base/dists/lognormal/logpdf","base.dists.lognormal.mean":"@stdlib/stats/base/dists/lognormal/mean","base.dists.lognormal.median":"@stdlib/stats/base/dists/lognormal/median","base.dists.lognormal.mode":"@stdlib/stats/base/dists/lognormal/mode","base.dists.lognormal.pdf":"@stdlib/stats/base/dists/lognormal/pdf","base.dists.lognormal.quantile":"@stdlib/stats/base/dists/lognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdli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araswamy/variance","base.dists.laplace.cdf":"@stdlib/stats/base/dists/laplace/cdf","base.dists.laplace.entropy":"@stdlib/stats/base/dists/laplace/entropy","base.dists.laplace.kurtosis":"@stdlib/stats/base/dists/laplace/kurtosis","base.dists.laplace.Laplace":"@stdlib/stats/base/dists/laplace/ctor","base.dists.laplace.logcdf":"@stdlib/stats/base/dists/laplace/logcdf","base.dists.laplace.logpdf":"@stdlib/stats/base/dists/laplace/logpdf","base.dists.laplace.mean":"@stdlib/stats/base/dists/laplace/mean","base.dists.laplace.median":"@stdlib/stats/base/dists/laplace/median","base.dists.laplace.mgf":"@stdlib/stats/base/dists/laplace/mgf","base.dists.laplace.mode":"@stdlib/stats/base/dists/laplace/mode","base.dists.laplace.pdf":"@stdlib/stats/base/dists/laplace/pdf","base.dists.laplace.quantile":"@stdlib/stats/base/dists/laplace/quantile","base.dists.laplace.skewness":"@stdlib/stats/base/dists/laplace/skewness","base.dists.laplace.stdev":"@stdlib/stats/base/dists/laplace/stdev","base.dists.laplace.variance":"@stdlib/stats/base/dists/laplace/variance","base.dists.levy.cdf":"@stdlib/stats/base/dists/levy/cdf","base.dists.levy.entropy":"@stdlib/stats/base/dists/levy/entropy","base.dists.levy.Levy":"@stdlib/stats/base/dists/levy/ctor","base.dists.levy.logcdf":"@stdlib/stats/base/dists/levy/logcdf","base.dists.levy.logpdf":"@stdlib/stats/base/dists/levy/logpdf","base.dists.levy.mean":"@stdlib/stats/base/dists/levy/mean","base.dists.levy.median":"@stdlib/stats/base/dists/levy/median","base.dists.levy.mode":"@stdlib/stats/base/dists/levy/mode","base.dists.levy.pdf":"@stdlib/stats/base/dists/levy/pdf","base.dists.levy.quantile":"@stdlib/stats/base/dists/levy/quantile","base.dists.levy.stdev":"@stdlib/stats/base/dists/levy/stdev","base.dists.levy.variance":"@stdlib/stats/base/dists/levy/variance","base.dists.logistic.cdf":"@stdlib/stats/base/dists/logistic/cdf","base.dists.logistic.entropy":"@stdlib/stats/base/dists/logistic/entropy","base.dists.logistic.kurtosis":"@stdlib/stats/base/dists/logistic/kurtosis","base.dists.logistic.logcdf":"@stdlib/stats/base/dists/logistic/logcdf","base.dists.logistic.Logistic":"@stdlib/stats/base/dists/logistic/ctor","base.dists.logistic.logpdf":"@stdlib/stats/base/dists/logistic/logpdf","base.dists.logistic.mean":"@stdlib/stats/base/dists/logistic/mean","base.dists.logistic.median":"@stdlib/stats/base/dists/logistic/median","base.dists.logistic.mgf":"@stdlib/stats/base/dists/logistic/mgf","base.dists.logistic.mode":"@stdlib/stats/base/dists/logistic/mode","base.dists.logistic.pdf":"@stdlib/stats/base/dists/logistic/pdf","base.dists.logistic.quantile":"@stdlib/stats/base/dists/logistic/quantile","base.dists.logistic.skewness":"@stdlib/stats/base/dists/logistic/skewness","base.dists.logistic.stdev":"@stdlib/stats/base/dists/logistic/stdev","base.dists.logistic.variance":"@stdlib/stats/base/dists/logistic/variance","base.dists.lognormal.cdf":"@stdlib/stats/base/dists/lognormal/cdf","base.dists.lognormal.entropy":"@stdlib/stats/base/dists/lognormal/entropy","base.dists.lognormal.kurtosis":"@stdlib/stats/base/dists/lognormal/kurtosis","base.dists.lognormal.LogNormal":"@stdlib/stats/base/dists/lognormal/ctor","base.dists.lognormal.logpdf":"@stdlib/stats/base/dists/lognormal/logpdf","base.dists.lognormal.mean":"@stdlib/stats/base/dists/lognormal/mean","base.dists.lognormal.median":"@stdlib/stats/base/dists/lognormal/median","base.dists.lognormal.mode":"@stdlib/stats/base/dists/lognormal/mode","base.dists.lognormal.pdf":"@stdlib/stats/base/dists/lognormal/pdf","base.dists.lognormal.quantile":"@stdlib/stats/base/dists/lognormal/quantile","base.dists.lognormal.skewness":"@stdlib/stats/base/dists/lognormal/skewness","base.dists.lognormal.stdev":"@stdlib/stats/base/dists/lognormal/stdev","base.dists.lognormal.variance":"@stdlib/stats/base/dists/lognormal/variance","base.dists.negativeBinomial.cdf":"@stdlib/stats/base/dists/negative-binomial/cdf","base.dists.negativeBinomial.kurtosis":"@stdlib/stats/base/dists/negative-binomial/kurtosis","base.dists.negativeBinomial.logpmf":"@stdlib/stats/base/dists/negative-binomial/logpmf","base.dists.negativeBinomial.mean":"@stdlib/stats/base/dists/negative-binomial/mean","base.dists.negativeBinomial.mgf":"@stdlib/stats/base/dists/negative-binomial/mgf","base.dists.negativeBinomial.mode":"@stdlib/stats/base/dists/negative-binomial/mode","base.dists.negativeBinomial.NegativeBinomial":"@stdlib/stats/base/dists/negative-binomial/ctor","base.dists.negativeBinomial.pmf":"@stdlib/stats/base/dists/negative-binomial/pmf","base.dists.negativeBinomial.quantile":"@stdlib/stats/base/dists/negative-binomial/quantile","base.dists.negativeBinomial.skewness":"@stdlib/stats/base/dists/negative-binomial/skewness","base.dists.negativeBinomial.stdev":"@stdlib/stats/base/dists/negative-binomial/stdev","base.dists.negativeBinomial.variance":"@stdlib/stats/base/dists/negative-binomial/variance","base.dists.normal.cdf":"@stdlib/stats/base/dists/normal/cdf","base.dists.normal.entropy":"@stdli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ht","splitStream":"@stdlib/streams/node/split","SQRT_EPS":"@stdlib/constants/math/float64-sqrt-eps","SQRT_HALF":"@stdlib/constants/math/float64-sqrt-half","SQRT_HALF_PI":"@stdlib/constants/math/float64-sqrt-half-pi","SQRT_PHI":"@stdlib/constants/math/float64-sqrt-phi","SQRT_PI":"@stdlib/constants/math/float64-sqrt-pi","SQRT_THREE":"@stdlib/constants/math/float64-sqrt-three","SQRT_TWO":"@stdlib/constants/math/float64-sqrt-two","SQRT_TWO_PI":"@stdlib/constants/math/float64-sqrt-two-pi","Stack":"@stdlib/utils/stack","startcase":"@stdlib/string/startcase","startsWith":"@stdlib/string/starts-with","STOPWORDS_EN":"@stdlib/datasets/stopwords-en","stridedarray2iterator":"@stdlib/array/to-strided-iterator","stridedArrayStream":"@stdlib/streams/node/from-strided-array","string2buffer":"@stdlib/buffer/from-string","sub2ind":"@stdlib/ndarray/sub2ind","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-multi-hop-sensor-network","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-single-hop-sensor-network","Symbol":"@stdlib/symbol/ctor","tabulate":"@stdlib/utils/tabulate","tabulateBy":"@stdlib/utils/tabulate-by","tabulateByAsync":"@stdlib/utils/async/tabulate-by","tic":"@stdlib/time/tic","timeit":"@stdlib/utils/timeit","tmpdir":"@stdlib/os/tmpdir","toc":"@stdlib/time/toc","tokenize":"@stdlib/nlp/tokenize","transformStream":"@stdlib/streams/node/transform","trim":"@stdlib/string/trim","trycatch":"@stdlib/utils/try-catch","trycatchAsync":"@stdlib/utils/async/try-catch","tryFunction":"@stdlib/utils/try-function","tryRequire":"@stdlib/utils/try-require","trythen":"@stdlib/utils/try-then","trythenAsync":"@stdlib/utils/async/try-then","ttest":"@stdlib/stats/ttest","ttest2":"@stdlib/stats/ttest2","TWO_PI":"@stdlib/constants/math/float64-two-pi","typedarray":"@stdlib/array/typed","typedarray2json":"@stdlib/array/to-json","typedarrayComplexCtors":"@stdlib/array/typed-complex-ctors","typedarrayComplexDataTypes":"@stdlib/array/typed-complex-dtypes","typedarrayCtors":"@stdlib/array/typed-ctors","typedarrayDataTypes":"@stdlib/array/typed-dtypes","typedarraypool":"@stdlib/array/pool","typemax":"@stdlib/utils/type-max","typemin":"@stdlib/utils/type-min","typeOf":"@stdlib/utils/type-of","UINT8_MAX":"@stdlib/constants/math/uint8-max","UINT8_NUM_BYTES":"@stdlib/constants/math/uint8-num-bytes","Uint8Array":"@stdlib/array/uint8","Uint8ClampedArray":"@stdlib/array/uint8c","UINT16_MAX":"@stdlib/constants/math/uint16-max","UINT16_NUM_BYTES":"@stdlib/constants/math/uint16-num-bytes","Uint16Array":"@stdlib/array/uint16","UINT32_MAX":"@stdlib/constants/math/uint32-max","UINT32_NUM_BYTES":"@stdlib/constants/math/uint32-num-bytes","Uint32Array":"@stdlib/array/uint32","umask":"@stdlib/process/umask","uncapitalize":"@stdlib/string/uncapitalize","uncapitalizeKeys":"@stdlib/utils/uncapitalize-keys","uncurry":"@stdlib/utils/uncurry","uncurryRight":"@stdlib/utils/uncurry-right","UNICODE_MAX":"@stdlib/constants/string/unicode-max","UNICODE_MAX_BMP":"@stdlib/constants/string/unicode-max-bmp","UnicodeColumnChartSparkline":"@stdlib/plot/sparklines/unicode/column","UnicodeLineChartSparkline":"@stdlib/plot/sparklines/unicode/line","UnicodeSparkline":"@stdlib/plot/sparklines/unicode","UnicodeTristateChartSparkline":"@stdlib/plot/sparklines/unicode/tristate","UnicodeUpDownChartSparkline":"@stdlib/plot/sparklines/unicode/up-down","UnicodeWinLossChartSparkline":"@stdlib/plot/sparklines/unicode/win-loss","unlink":"@stdlib/fs/unlink","unshift":"@stdlib/utils/unshift","until":"@stdlib/utils/until","untilAsync":"@stdlib/utils/async/until","untilEach":"@stdlib/utils/until-each","untilEachRight":"@stdlib/utils/until-each-right","unzip":"@stdlib/utils/unzip","uppercase":"@stdlib/string/uppercase","uppercaseKeys":"@stdlib/utils/uppercase-keys","US_STATES_ABBR":"@stdlib/datasets/us-states-abbr","US_STATES_CAPITALS":"@stdlib/datasets/us-states-capitals","US_STATES_CAPITALS_NAMES":"@stdlib/datasets/us-states-capitals-names","US_STATES_NAMES":"@stdlib/datasets/us-states-names","US_STATES_NAMES_CAPITALS":"@stdlib/datasets/us-states-names-capitals","utf16ToUTF8Array":"@stdlib/string/utf16-to-utf8-array","vartest":"@stdlib/stats/vartest","waterfall":"@stdlib/utils/async/series-waterfall","whileAsync":"@stdlib/utils/async/while","whileEach":"@stdlib/utils/while-each","whileEachRight":"@stdlib/utils/while-each-right","whilst":"@stdlib/utils/while","writableProperties":"@stdlib/utils/writable-properties","writablePropertiesIn":"@stdlib/utils/writable-properties-in","writablePropertyNames":"@stdlib/utils/writable-property-names","writablePropertyNamesIn":"@stdlib/utils/writable-property-names-in","writablePropertySymbols":"@stdlib/utils/writable-property-symbols","writablePropertySymbolsIn":"@stdlib/utils/writable-property-symbols-in","writeFile":"@stdlib/fs/write-file","zip":"@stdlib/utils/zip","ztest":"@stdlib/stats/ztest","ztest2":"@stdlib/stats/ztest2"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv index 99a93407e367..7f7cf6d0dfd4 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv @@ -852,7 +852,7 @@ deepHasOwnProp,"deepHasProp,hasOwnProp,deepGet,deepPluck,deepSet" deepHasProp,"deepHasOwnProp,hasOwnProp,deepGet,deepPluck,deepSet" deepPluck,"deepGet,deepSet" deepSet,"deepGet,deepPluck" -defineMemoizedProperty,"defineProperty" +defineMemoizedProperty,"setMemoizedReadOnly,defineProperty" defineProperties,"defineProperty,setReadOnly" defineProperty,"defineProperties,setReadOnly" dirname,"extname" @@ -1764,6 +1764,7 @@ setConfigurableReadOnly,"setConfigurableReadOnlyAccessor,setConfigurableReadWrit setConfigurableReadOnlyAccessor,"setConfigurableReadOnly,setConfigurableReadWriteAccessor,setConfigurableWriteOnlyAccessor,defineProperty,setReadOnlyAccessor" setConfigurableReadWriteAccessor,"setConfigurableReadOnly,setConfigurableReadOnlyAccessor,setConfigurableWriteOnlyAccessor,defineProperty,setReadWriteAccessor" setConfigurableWriteOnlyAccessor,"setConfigurableReadOnly,setConfigurableReadOnlyAccessor,setConfigurableReadWriteAccessor,defineProperty,setWriteOnlyAccessor" +setMemoizedReadOnly,"defineMemoizedProperty,setReadOnly" setNonEnumerableProperty,"setNonEnumerableReadOnlyAccessor,setNonEnumerableReadOnly,setNonEnumerableReadWriteAccessor,setNonEnumerableWriteOnlyAccessor,setReadOnly" setNonEnumerableReadOnly,"setNonEnumerableProperty,setNonEnumerableReadOnlyAccessor,setNonEnumerableReadWriteAccessor,setNonEnumerableWriteOnlyAccessor,setReadOnly" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index a5d1c15a7945..8b32e11826db 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1764,6 +1764,7 @@ setConfigurableReadOnly setConfigurableReadOnlyAccessor setConfigurableReadWriteAccessor setConfigurableWriteOnlyAccessor +setMemoizedReadOnly setNonEnumerableProperty setNonEnumerableReadOnly setNonEnumerableReadOnlyAccessor diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/s.js b/lib/node_modules/@stdlib/namespace/lib/namespace/s.js index e89267e2a5c3..4f0e467bfcdc 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/s.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/s.js @@ -221,6 +221,17 @@ ns.push({ ] }); +ns.push({ + 'alias': 'setMemoizedReadOnly', + 'path': '@stdlib/utils/define-memoized-read-only-property', + 'value': require( '@stdlib/utils/define-memoized-read-only-property' ), + 'type': 'Function', + 'related': [ + '@stdlib/utils/define-memoized-property', + '@stdlib/utils/define-read-only-property' + ] +}); + ns.push({ 'alias': 'setNonEnumerableProperty', 'path': '@stdlib/utils/define-nonenumerable-property', diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index 470bbca12ab0..b045f5ac7f4b 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -1764,6 +1764,7 @@ "@stdlib/utils/define-configurable-read-only-accessor",setConfigurableReadOnlyAccessor "@stdlib/utils/define-configurable-read-write-accessor",setConfigurableReadWriteAccessor "@stdlib/utils/define-configurable-write-only-accessor",setConfigurableWriteOnlyAccessor +"@stdlib/utils/define-memoized-read-only-property",setMemoizedReadOnly "@stdlib/utils/define-nonenumerable-property",setNonEnumerableProperty "@stdlib/utils/define-nonenumerable-read-only-property",setNonEnumerableReadOnly "@stdlib/utils/define-nonenumerable-read-only-accessor",setNonEnumerableReadOnlyAccessor diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index 6d7ba140cd5c..8c406f657bb6 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ 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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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araswamy.variance","@stdlib/stats/base/dists/laplace/cdf":"base.dists.laplace.cdf","@stdlib/stats/base/dists/laplace/entropy":"base.dists.laplace.entropy","@stdlib/stats/base/dists/laplace/kurtosis":"base.dists.laplace.kurtosis","@stdlib/stats/base/dists/laplace/ctor":"base.dists.laplace.Laplace","@stdlib/stats/base/dists/laplace/logcdf":"base.dists.laplace.logcdf","@stdlib/stats/base/dists/laplace/logpdf":"base.dists.laplace.logpdf","@stdlib/stats/base/dists/laplace/mean":"base.dists.laplace.mean","@stdlib/stats/base/dists/laplace/median":"base.dists.laplace.median","@stdlib/stats/base/dists/laplace/mgf":"base.dists.laplace.mgf","@stdlib/stats/base/dists/laplace/mode":"base.dists.laplace.mode","@stdlib/stats/base/dists/laplace/pdf":"base.dists.laplace.pdf","@stdlib/stats/base/dists/laplace/quantile":"base.dists.laplace.quantile","@stdlib/stats/base/dists/laplace/skewness":"base.dists.laplace.skewness","@stdlib/stats/base/dists/laplace/stdev":"base.dists.laplace.stdev","@stdlib/stats/base/dists/laplace/variance":"base.dists.laplace.variance","@stdlib/stats/base/dists/levy/cdf":"base.dists.levy.cdf","@stdlib/stats/base/dists/levy/entropy":"base.dists.levy.entropy","@stdlib/stats/base/dists/levy/ctor":"base.dists.levy.Levy","@stdlib/stats/base/dists/levy/logcdf":"base.dists.levy.logcdf","@stdlib/stats/base/dists/levy/logpdf":"base.dists.levy.logpdf","@stdlib/stats/base/dists/levy/mean":"base.dists.levy.mean","@stdlib/stats/base/dists/levy/median":"base.dists.levy.median","@stdlib/stats/base/dists/levy/mode":"base.dists.levy.mode","@stdlib/stats/base/dists/levy/pdf":"base.dists.levy.pdf","@stdlib/stats/base/dists/levy/quantile":"base.dists.levy.quantile","@stdlib/stats/base/dists/levy/stdev":"base.dists.levy.stdev","@stdlib/stats/base/dists/levy/variance":"base.dists.levy.variance","@stdlib/stats/base/dists/logistic/cdf":"base.dists.logistic.cdf","@stdlib/stats/base/dists/logistic/entropy":"base.dists.logistic.entropy","@stdlib/stats/base/dists/logistic/kurtosis":"base.dists.logistic.kurtosis","@stdlib/stats/base/dists/logistic/logcdf":"base.dists.logistic.logcdf","@stdlib/stats/base/dists/logistic/ctor":"base.dists.logistic.Logistic","@stdlib/stats/base/dists/logistic/logpdf":"base.dists.logistic.logpdf","@stdlib/stats/base/dists/logistic/mean":"base.dists.logistic.mean","@stdlib/stats/base/dists/logistic/median":"base.dists.logistic.median","@stdlib/stats/base/dists/logistic/mgf":"base.dists.logistic.mgf","@stdlib/stats/base/dists/logistic/mode":"base.dists.logistic.mode","@stdlib/stats/base/dists/logistic/pdf":"base.dists.logistic.pdf","@stdlib/stats/base/dists/logistic/quantile":"base.dists.logistic.quantile","@stdlib/stats/base/dists/logistic/skewness":"base.dists.logistic.skewness","@stdlib/stats/base/dists/logistic/stdev":"base.dists.logistic.stdev","@stdlib/stats/base/dists/logistic/variance":"base.dists.logistic.variance","@stdlib/stats/base/dists/lognormal/cdf":"base.dists.lognormal.cdf","@stdlib/stats/base/dists/lognormal/entropy":"base.dists.lognormal.entropy","@stdlib/stats/base/dists/lognormal/kurtosis":"base.dists.lognormal.kurtosis","@stdlib/stats/base/dists/lognormal/ctor":"base.dists.lognormal.LogNormal","@stdlib/stats/base/dists/lognormal/logpdf":"base.dists.lognormal.logpdf","@stdlib/stats/base/dists/lognormal/mean":"base.dists.lognormal.mean","@stdlib/stats/base/dists/lognormal/median":"base.dists.lognormal.median","@stdlib/stats/base/dists/lognormal/mode":"base.dists.lognormal.mode","@stdlib/stats/base/dists/lognormal/pdf":"base.dists.lognormal.pdf","@stdlib/stats/base/dists/lognormal/quantile":"base.dists.lognormal.quantile","@stdlib/stats/base/dists/lognormal/skewness":"base.dists.lognormal.skewness","@stdlib/stats/base/dists/lognormal/stdev":"base.dists.lognormal.stdev","@stdlib/stats/base/dists/lognormal/variance":"base.dists.lognormal.variance","@stdlib/stats/base/dists/negative-binomial/cdf":"base.dists.negativeBinomial.cdf","@stdlib/stats/base/dists/negative-binomial/kurtosis":"base.dists.negativeBinomial.kurtosis","@stdlib/stats/base/dists/negative-binomial/logpmf":"base.dists.negativeBinomial.logpmf","@stdlib/stats/base/dists/negative-binomial/mean":"base.dists.negativeBinomial.mean","@stdlib/stats/base/dists/negative-binomial/mgf":"base.dists.negativeBinomial.mgf","@stdlib/stats/base/dists/negative-binomial/mode":"base.dists.negativeBinomial.mode","@stdlib/stats/base/dists/negative-binomial/ctor":"base.dists.negativeBinomial.NegativeBinomial","@stdlib/stats/base/dists/negative-binomial/pmf":"base.dists.negativeBinomial.pmf","@stdlib/stats/base/dists/negative-binomial/quantile":"base.dists.negativeBinomial.quantile","@stdlib/stats/base/dists/negative-binomial/skewness":"base.dists.negativeBinomial.skewness","@stdlib/stats/base/dists/negative-binomial/stdev":"base.dists.negativeBinomial.stdev","@stdlib/stats/base/dists/negative-binomial/variance":"base.dists.negativeBinomial.variance","@stdlib/stats/base/dists/normal/cdf":"base.dists.normal.cdf","@stdlib/stats/base/dists/normal/en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ht","@stdlib/streams/node/split":"splitStream","@stdlib/constants/math/float64-sqrt-eps":"SQRT_EPS","@stdlib/constants/math/float64-sqrt-half":"SQRT_HALF","@stdlib/constants/math/float64-sqrt-half-pi":"SQRT_HALF_PI","@stdlib/constants/math/float64-sqrt-phi":"SQRT_PHI","@stdlib/constants/math/float64-sqrt-pi":"SQRT_PI","@stdlib/constants/math/float64-sqrt-three":"SQRT_THREE","@stdlib/constants/math/float64-sqrt-two":"SQRT_TWO","@stdlib/constants/math/float64-sqrt-two-pi":"SQRT_TWO_PI","@stdlib/utils/stack":"Stack","@stdlib/string/startcase":"startcase","@stdlib/string/starts-with":"startsWith","@stdlib/datasets/stopwords-en":"STOPWORDS_EN","@stdlib/array/to-strided-iterator":"stridedarray2iterator","@stdlib/streams/node/from-strided-array":"stridedArrayStream","@stdlib/buffer/from-string":"string2buffer","@stdlib/ndarray/sub2ind":"sub2ind","@stdlib/datasets/suthaharan-multi-hop-sensor-network":"SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","@stdlib/datasets/suthaharan-single-hop-sensor-network":"SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","@stdlib/symbol/ctor":"Symbol","@stdlib/utils/tabulate":"tabulate","@stdlib/utils/tabulate-by":"tabulateBy","@stdlib/utils/async/tabulate-by":"tabulateByAsync","@stdlib/time/tic":"tic","@stdlib/utils/timeit":"timeit","@stdlib/os/tmpdir":"tmpdir","@stdlib/time/toc":"toc","@stdlib/nlp/tokenize":"tokenize","@stdlib/streams/node/transform":"transformStream","@stdlib/string/trim":"trim","@stdlib/utils/try-catch":"trycatch","@stdlib/utils/async/try-catch":"trycatchAsync","@stdlib/utils/try-function":"tryFunction","@stdlib/utils/try-require":"tryRequire","@stdlib/utils/try-then":"trythen","@stdlib/utils/async/try-then":"trythenAsync","@stdlib/stats/ttest":"ttest","@stdlib/stats/ttest2":"ttest2","@stdlib/constants/math/float64-two-pi":"TWO_PI","@stdlib/array/typed":"typedarray","@stdlib/array/to-json":"typedarray2json","@stdlib/array/typed-complex-ctors":"typedarrayComplexCtors","@stdlib/array/typed-complex-dtypes":"typedarrayComplexDataTypes","@stdlib/array/typed-ctors":"typedarrayCtors","@stdlib/array/typed-dtypes":"typedarrayDataTypes","@stdlib/array/pool":"typedarraypool","@stdlib/utils/type-max":"typemax","@stdlib/utils/type-min":"typemin","@stdlib/utils/type-of":"typeOf","@stdlib/constants/math/uint8-max":"UINT8_MAX","@stdlib/constants/math/uint8-num-bytes":"UINT8_NUM_BYTES","@stdlib/array/uint8":"Uint8Array","@stdlib/array/uint8c":"Uint8ClampedArray","@stdlib/constants/math/uint16-max":"UINT16_MAX","@stdlib/constants/math/uint16-num-bytes":"UINT16_NUM_BYTES","@stdlib/array/uint16":"Uint16Array","@stdlib/constants/math/uint32-max":"UINT32_MAX","@stdlib/constants/math/uint32-num-bytes":"UINT32_NUM_BYTES","@stdlib/array/uint32":"Uint32Array","@stdlib/process/umask":"umask","@stdlib/string/uncapitalize":"uncapitalize","@stdlib/utils/uncapitalize-keys":"uncapitalizeKeys","@stdlib/utils/uncurry":"uncurry","@stdlib/utils/uncurry-right":"uncurryRight","@stdlib/constants/string/unicode-max":"UNICODE_MAX","@stdlib/constants/string/unicode-max-bmp":"UNICODE_MAX_BMP","@stdlib/plot/sparklines/unicode/column":"UnicodeColumnChartSparkline","@stdlib/plot/sparklines/unicode/line":"UnicodeLineChartSparkline","@stdlib/plot/sparklines/unicode":"UnicodeSparkline","@stdlib/plot/sparklines/unicode/tristate":"UnicodeTristateChartSparkline","@stdlib/plot/sparklines/unicode/up-down":"UnicodeUpDownChartSparkline","@stdlib/plot/sparklines/unicode/win-loss":"UnicodeWinLossChartSparkline","@stdlib/fs/unlink":"unlink","@stdlib/utils/unshift":"unshift","@stdlib/utils/until":"until","@stdlib/utils/async/until":"untilAsync","@stdlib/utils/until-each":"untilEach","@stdlib/utils/until-each-right":"untilEachRight","@stdlib/utils/unzip":"unzip","@stdlib/string/uppercase":"uppercase","@stdlib/utils/uppercase-keys":"uppercaseKeys","@stdlib/datasets/us-states-abbr":"US_STATES_ABBR","@stdlib/datasets/us-states-capitals":"US_STATES_CAPITALS","@stdlib/datasets/us-states-capitals-names":"US_STATES_CAPITALS_NAMES","@stdlib/datasets/us-states-names":"US_STATES_NAMES","@stdlib/datasets/us-states-names-capitals":"US_STATES_NAMES_CAPITALS","@stdlib/string/utf16-to-utf8-array":"utf16ToUTF8Array","@stdlib/stats/vartest":"vartest","@stdlib/utils/async/series-waterfall":"waterfall","@stdlib/utils/async/while":"whileAsync","@stdlib/utils/while-each":"whileEach","@stdlib/utils/while-each-right":"whileEachRight","@stdlib/utils/while":"whilst","@stdlib/utils/writable-properties":"writableProperties","@stdlib/utils/writable-properties-in":"writablePropertiesIn","@stdlib/utils/writable-property-names":"writablePropertyNames","@stdlib/utils/writable-property-names-in":"writablePropertyNamesIn","@stdlib/utils/writable-property-symbols":"writablePropertySymbols","@stdlib/utils/writable-property-symbols-in":"writablePropertySymbolsIn","@stdlib/fs/write-file":"writeFile","@stdlib/utils/zip":"zip","@stdlib/stats/ztest":"ztest","@stdlib/stats/ztest2":"ztest2"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv index d89becfbd8d1..9336632791aa 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv @@ -852,7 +852,7 @@ "@stdlib/assert/deep-has-property","@stdlib/assert/deep-has-own-property,@stdlib/assert/has-own-property,@stdlib/utils/deep-get,@stdlib/utils/deep-pluck,@stdlib/utils/deep-set" "@stdlib/utils/deep-pluck","@stdlib/utils/deep-get,@stdlib/utils/deep-set" "@stdlib/utils/deep-set","@stdlib/utils/deep-get,@stdlib/utils/deep-pluck" -"@stdlib/utils/define-memoized-property","@stdlib/utils/define-property" +"@stdlib/utils/define-memoized-property","@stdlib/utils/define-memoized-read-only-property,@stdlib/utils/define-property" "@stdlib/utils/define-properties","@stdlib/utils/define-property,@stdlib/utils/define-read-only-property" "@stdlib/utils/define-property","@stdlib/utils/define-properties,@stdlib/utils/define-read-only-property" "@stdlib/utils/dirname","@stdlib/utils/extname" @@ -1764,6 +1764,7 @@ "@stdlib/utils/define-configurable-read-only-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-configurable-read-write-accessor,@stdlib/utils/define-configurable-write-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-read-only-accessor" "@stdlib/utils/define-configurable-read-write-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-configurable-read-only-accessor,@stdlib/utils/define-configurable-write-only-accessor,@stdlib/utils/define-property,@stdlib/utils/define-read-write-accessor" "@stdlib/utils/define-configurable-write-only-accessor","@stdlib/utils/define-configurable-read-only-property,@stdlib/utils/define-configurable-read-only-accessor,@stdlib/utils/define-configurable-read-write-accessor,@stdlib/utils/define-property,@stdlib/utils/define-write-only-accessor" +"@stdlib/utils/define-memoized-read-only-property","@stdlib/utils/define-memoized-property,@stdlib/utils/define-read-only-property" "@stdlib/utils/define-nonenumerable-property","@stdlib/utils/define-nonenumerable-read-only-accessor,@stdlib/utils/define-nonenumerable-read-only-property,@stdlib/utils/define-nonenumerable-read-write-accessor,@stdlib/utils/define-nonenumerable-write-only-accessor,@stdlib/utils/define-read-only-property" 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js index 3fa516430272..e4877723fd71 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js @@ -1781,6 +1781,7 @@ var db = { "setConfigurableReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", "setConfigurableReadWriteAccessor": "obj = {};\nname = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n", "setConfigurableWriteOnlyAccessor": "obj = {};\nval = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n", + "setMemoizedReadOnly": "obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n", "setNonEnumerableProperty": "obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n", "setNonEnumerableReadOnly": "obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", "setNonEnumerableReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js index 109bdec9d625..3676856ba4b1 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ b/lib/node_modules/@stdlib/repl/help/lib/db.js @@ -873,7 +873,7 @@ var db = { "deepHasProp": "\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n", "deepPluck": "\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n", "deepSet": "\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n", - "defineMemoizedProperty": "\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineProperty\n", + "defineMemoizedProperty": "\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n", "defineProperties": "\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n", "defineProperty": "\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n", "dirname": "\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n", @@ -1782,6 +1782,7 @@ var db = { "setConfigurableReadOnlyAccessor": "\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n", "setConfigurableReadWriteAccessor": "\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n", "setConfigurableWriteOnlyAccessor": "\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n", + "setMemoizedReadOnly": "\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n", "setNonEnumerableProperty": "\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", "setNonEnumerableReadOnly": "\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", "setNonEnumerableReadOnlyAccessor": "\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n", From 1c48dc1d2b84a150621670188295037f2eebd64a Mon Sep 17 00:00:00 2001 From: kgryte Date: Sun, 17 Mar 2019 01:48:27 -0700 Subject: [PATCH 095/142] Update examples --- .../@stdlib/utils/define-memoized-property/README.md | 2 +- .../@stdlib/utils/define-memoized-property/examples/index.js | 2 +- .../utils/define-memoized-read-only-property/examples/index.js | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/README.md b/lib/node_modules/@stdlib/utils/define-memoized-property/README.md index b88384e58e30..5a79703c452b 100644 --- a/lib/node_modules/@stdlib/utils/define-memoized-property/README.md +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/README.md @@ -92,10 +92,10 @@ function Foo() { return new Foo(); } self = this; + this.count = 0; defineMemoizedProperty( this, 'fibo', { 'value': fibo }); - this.count = 0; return this; function fibo() { diff --git a/lib/node_modules/@stdlib/utils/define-memoized-property/examples/index.js b/lib/node_modules/@stdlib/utils/define-memoized-property/examples/index.js index bc240d5d8d7c..1c3380260c45 100644 --- a/lib/node_modules/@stdlib/utils/define-memoized-property/examples/index.js +++ b/lib/node_modules/@stdlib/utils/define-memoized-property/examples/index.js @@ -27,10 +27,10 @@ function Foo() { return new Foo(); } self = this; + this.count = 0; defineMemoizedProperty( this, 'fibo', { 'value': fibo }); - this.count = 0; return this; function fibo() { diff --git a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/examples/index.js b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/examples/index.js index 51b218866927..9fdd11b5fcab 100644 --- a/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/examples/index.js +++ b/lib/node_modules/@stdlib/utils/define-memoized-read-only-property/examples/index.js @@ -27,8 +27,8 @@ function Foo() { return new Foo(); } self = this; - setMemoizedReadOnly( this, 'fibo', fibo ); this.count = 0; + setMemoizedReadOnly( this, 'fibo', fibo ); return this; function fibo() { From 2dbf9d492dc91f35dd5208e55b2baff6ad399003 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 03:10:05 -0700 Subject: [PATCH 096/142] Set alias accessors on context object and remove utils --- ...ad_only_property.js => create_accessor.js} | 34 +-- .../@stdlib/repl/ctor/lib/create_context.js | 218 ++++++++++++++---- .../define_configurable_read_only_accessor.js | 47 ---- .../@stdlib/repl/ctor/lib/help_text.js | 12 +- .../@stdlib/repl/ctor/lib/main.js | 25 +- 5 files changed, 220 insertions(+), 116 deletions(-) rename lib/node_modules/@stdlib/repl/ctor/lib/{define_configurable_read_only_property.js => create_accessor.js} (57%) delete mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_accessor.js diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_property.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js similarity index 57% rename from lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_property.js rename to lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js index 0de1a877861a..6fcfbb8a9edf 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_property.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js @@ -18,31 +18,31 @@ 'use strict'; -// MODULES // - -var defineProperty = require( '@stdlib/utils/define-property' ); - - // MAIN // /** -* Defines a configurable non-enumerable read-only property. +* Returns an accessor for loading an underlying implementation upon first access. * * @private -* @param {Object} obj - object on which to define the property -* @param {(string|symbol)} prop - property -* @param {*} value - value to assign +* @param {Function} require - context `require` function +* @param {string} pkg - package name +* @returns {Function} get accessor */ -function setConfigurableReadOnly( obj, prop, value ) { - defineProperty( obj, prop, { - 'configurable': true, - 'enumerable': false, - 'writable': false, - 'value': value - }); +function createAccessor( require, pkg ) { + return get; + + /** + * Returns an underlying implementation. + * + * @private + * @returns {*} package export + */ + function get() { + return require( pkg ); // eslint-disable-line stdlib/no-dynamic-require + } } // EXPORTS // -module.exports = setConfigurableReadOnly; +module.exports = createAccessor; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index a0be5a5db4ba..ddbd31252557 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -30,13 +30,15 @@ var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var getGlobal = require( '@stdlib/utils/global' ); var objectKeys = require( '@stdlib/utils/keys' ); -var defineProperty = require( '@stdlib/utils/define-property' ); -var setNonEnumerable = require( '@stdlib/utils/define-nonenumerable-property' ); -var setNonEnumerableReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); -var setNonEnumerableReadOnlyAccessor = require( '@stdlib/utils/define-nonenumerable-read-only-accessor' ); // eslint-disable-line id-length -var setConfigurableReadOnly = require( './define_configurable_read_only_property.js' ); -var setConfigurableReadOnlyAccessor = require( './define_configurable_read_only_accessor.js' ); // eslint-disable-line id-length +var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); +var setReadOnlyAccessor = require( '@stdlib/utils/define-read-only-accessor' ); +var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); +var setConfigurableReadOnlyAccessor = require( '@stdlib/utils/define-configurable-read-only-accessor' ); // eslint-disable-line id-length +var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); var createRequire = require( './create_require.js' ); +var createAccessor = require( './create_accessor.js' ); var HELP_TEXT = require( './help_text.js' ); var GLOBALS = require( './globals.js' ); @@ -48,6 +50,151 @@ var debug = logger( 'repl:context' ); // Cache references to module methods (WARNING: use of *private* methods exposed on the `Module` object; thus, breakage is possible!): var resolveLookupPaths = Module._resolveLookupPaths; +// Cache the list of aliases: +var ALIASES = aliases(); // NOTE: we assume all aliases are unique (no duplicates!) + + +// FUNCTIONS // + +/** +* Sets commands on a sandboxed `context` object. +* +* @private +* @param {Object} context - context object +* @param {ArrayArray} commands - commands +* @returns {Object} context object +*/ +function setCommands( context, commands ) { + var cmd; + var i; + + for ( i = 0; i < commands.length; i++ ) { + cmd = commands[ i ]; + if ( cmd[ 2 ] ) { + setReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); + } else { + setReadOnly( context, cmd[ 0 ], cmd[ 1 ] ); + } + } + return context; +} + +/** +* Sets aliases on a sandboxed `context` object. +* +* @private +* @param {Object} context - context object +* @returns {Object} context object +*/ +function setAliases( context ) { + var key; + var pkg; + var o; + var i; + var j; + var k; + + // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to recursively generate nested objects... + for ( i = 0; i < ALIASES.length; i++ ) { + o = context; + key = ALIASES[ i ].split( '.' ); + for ( j = 0; j < key.length-1; j++ ) { + k = key[ j ]; + if ( !hasOwnProp( o, k ) ) { + setReadOnly( o, k, {} ); + } + o = o[ k ]; + } + k = key[ j ]; + pkg = alias2pkg( ALIASES[ i ] ); + setMemoizedReadOnly( o, k, createAccessor( context.require, pkg ) ); + } + return context; +} + +/** +* Sets commands on non-sandboxed `context` object. +* +* ## Notes +* +* - This function avoids overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects. +* +* @private +* @param {Array} out - output array for storing a list of global variables added to the global namespace +* @param {Object} context - context object +* @param {ArrayArray} commands - commands +* @returns {Object} context object +*/ +function setCommandsGlobal( out, context, commands ) { + var cmd; + var i; + + for ( i = 0; i < commands.length; i++ ) { + cmd = commands[ i ]; + if ( !hasOwnProp( context, cmd[ 0 ] ) ) { + out.push( cmd[ 0 ] ); + if ( cmd[ 2 ] ) { + setConfigurableReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); + } else { + setConfigurableReadOnly( context, cmd[ 0 ], cmd[ 1 ] ); + } + } + } + return context; +} + +/** +* Sets aliases on a non-sandboxed `context` object. +* +* ## Notes +* +* - This function avoids overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects. +* +* @private +* @param {Array} out - output array for storing a list of global variables added to the global namespace +* @param {Object} context - context object +* @returns {Object} context object +*/ +function setAliasesGlobal( out, context ) { + var key; + var FLG; + var pkg; + var o; + var i; + var j; + var k; + + // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to recursively generate nested objects... + for ( i = 0; i < ALIASES.length; i++ ) { + o = context; + FLG = false; + key = ALIASES[ i ].split( '.' ); + for ( j = 0; j < key.length-1; j++ ) { + k = key[ j ]; + if ( !hasOwnProp( o, k ) ) { + // Upon first encountering a new property, we need to remember the current key path, so that we can later remove the properties upon closing the REPL... + if ( FLG === false ) { + FLG = true; + out.push( key.slice( 0, j+1 ).join( '.' ) ); + } + setReadOnly( o, k, {} ); + } + o = o[ k ]; + } + k = key[ j ]; + + // Avoid overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects (e.g., don't break an already running application which has already defined a particular global variable)... + if ( !hasOwnProp( o, k ) ) { + if ( FLG === false ) { + out.push( ALIASES[ i ] ); + } + pkg = alias2pkg( ALIASES[ i ] ); + setMemoizedReadOnly( o, k, createAccessor( context.require, pkg ) ); + } + } + return context; +} + // MAIN // @@ -63,7 +210,6 @@ function createContext( repl ) { var Global; var keys; var cmds; - var cmd; var i; debug( 'Creating REPL execution context...' ); @@ -76,42 +222,36 @@ function createContext( repl ) { // Assign globals from the current global context to the sandboxed context (note: shallow copy!)... keys = objectKeys( GLOBALS ); for ( i = 0; i < keys.length; i++ ) { - setNonEnumerable( context, keys[ i ], GLOBALS[ keys[ i ] ] ); + setReadOnly( context, keys[ i ], GLOBALS[ keys[ i ] ] ); } - // Create a circular reference as in Node.js: - context.global = context; + setReadOnly( context, 'global', context ); // Create a new `console` interface: - setNonEnumerable( context, 'console', new Console( repl._ostream ) ); + setReadOnly( context, 'console', new Console( repl._ostream ) ); // Create a new `module` object: - setNonEnumerable( context, 'module', new Module( '' ) ); + setReadOnly( context, 'module', new Module( '' ) ); // Create a new `require` function: - setNonEnumerable( context, 'require', createRequire( context.module ) ); + setReadOnly( context, 'require', createRequire( context.module ) ); } else { context = Global; // Create a new `module` object: - defineProperty( context, 'module', { - 'configurable': true, - 'writable': false, - 'enumerable': false, - 'value': new Module( '' ) - }); + setConfigurableReadOnly( context, 'module', new Module( '' ) ); // Create a new `require` function: - defineProperty( context, 'require', { - 'configurable': true, - 'writable': false, - 'enumerable': false, - 'value': createRequire( context.module ) - }); + setConfigurableReadOnly( context, 'require', createRequire( context.module ) ); } context.module.paths = resolveLookupPaths( '', module, true ) || []; - // TODO: lazy load project APIs (configurable, enumerable(?) accessors which overwrite themselves to become read-only properties; see https://github.com/nodejs/node/blob/0c1e93b9efadfc9fae74907a631908477c7d085e/lib/internal/modules/cjs/helpers.js#L102) + // Add project APIs... + if ( repl._sandbox ) { + setAliases( context ); + } else { + setAliasesGlobal( repl._globalVars, context ); + } // Define a list of REPL-specific commands (NOTE: keep in alphabetical order): cmds = [ @@ -123,6 +263,10 @@ function createContext( repl ) { [ 'quit', onQuit, false ] ]; + // TODO: add `alias2pkg` command wrapper + + // TODO: add `alias2related` command wrapper + // TODO: add `example` command // TODO: add `isKeyword` command @@ -147,27 +291,9 @@ function createContext( repl ) { // Add commands requiring privileged access to internal instance variables... if ( repl._sandbox ) { - for ( i = 0; i < cmds.length; i++ ) { - cmd = cmds[ i ]; - if ( cmd[ 2 ] ) { - setNonEnumerableReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); - } else { - setNonEnumerableReadOnly( context, cmd[ 0 ], cmd[ 1 ] ); - } - } + setCommands( context, cmds ); } else { - for ( i = 0; i < cmds.length; i++ ) { - cmd = cmds[ i ]; - - // Avoid overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects... - if ( !hasOwnProp( context, cmd[ 0 ] ) ) { - if ( cmd[ 2 ] ) { - setConfigurableReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); // eslint-disable-line max-len - } else { - setConfigurableReadOnly( context, cmd[ 0 ], cmd[ 1 ] ); - } - } - } + setCommandsGlobal( repl._globalVars, context, cmds ); } return context; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_accessor.js b/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_accessor.js deleted file mode 100644 index c5c053d3cfff..000000000000 --- a/lib/node_modules/@stdlib/repl/ctor/lib/define_configurable_read_only_accessor.js +++ /dev/null @@ -1,47 +0,0 @@ -/** -* @license Apache-2.0 -* -* Copyright (c) 2019 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -'use strict'; - -// MODULES // - -var defineProperty = require( '@stdlib/utils/define-property' ); - - -// MAIN // - -/** -* Defines a configurable non-enumerable read-only accessor. -* -* @private -* @param {Object} obj - object on which to define the accessor -* @param {(string|symbol)} prop - property -* @param {Function} accessor - accessor function -*/ -function setConfigurableReadOnlyAccessor( obj, prop, accessor ) { // eslint-disable-line id-length - defineProperty( obj, prop, { - 'configurable': true, - 'enumerable': false, - 'get': accessor - }); -} - - -// EXPORTS // - -module.exports = setConfigurableReadOnlyAccessor; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js b/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js index 8d659bfd0dae..6e4a9175a5e5 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/help_text.js @@ -29,11 +29,6 @@ var MSG = [ ' example( alias ) Runs examples for a specified alias.', ' example( alias. ) Runs examples for a specified property.', '', - ' aliases() Lists namespace contents.', - ' alias2pkg( alias ) Converts an alias to a stdlib package name.', - ' pkg2alias( pkg ) Converts a stdlib package name to an alias.', - ' isKeyword( value ) Asserts whether a value is a reserved keyword/alias.', - '', ' load( fpath ) Loads and evaluates a JavaScript file line-by-line.', ' save( fpath ) Saves previous commands to a specified file.', ' saveStart( fpath ) Start saving commands to a specified file.', @@ -42,6 +37,13 @@ var MSG = [ ' clear() Clears the REPL context.', ' quit() Exits the REPL.', '', + ' aliases() Lists namespace contents.', + ' alias2pkg( alias ) Converts an alias to a stdlib package name.', + ' pkg2alias( pkg ) Converts a stdlib package name to an alias.', + ' alias2related( alias ) Lists related aliases.', + ' pkg2related( pkg ) Lists related package names.', + ' isKeyword( value ) Asserts whether a value is a reserved keyword/alias.', + '', ' citation() Prints how to cite stdlib in publications.', ' license() Prints license information.', ' copyright() Prints copyright information.', diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index 85b7d2224b11..b986dd24eb2c 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -125,6 +125,9 @@ function REPL( options ) { // Initialize an internal buffer for saving regular expression matches between command evaluations: setNonEnumerableReadOnly( this, '_regexp', [ '', '', '', '', '', '', '', '', '', '' ] ); + // For non-sandboxed REPLs, initialize an internal buffer for storing a list of global variables which need to be deleted upon closing a REPL in order to allow garbage collection and prevent memory leaks: + setNonEnumerableReadOnly( this, '_globalVars', ( this._sandbox ) ? null : [] ); + // Initialize an internal flag indicating whether the REPL has been closed: setNonEnumerable( this, '_closed', false ); @@ -168,7 +171,9 @@ function REPL( options ) { * @param {string} line - line data */ function onLine( line ) { - processLine( self, line ); + if ( self._closed === false ) { + processLine( self, line ); + } } /** @@ -283,8 +288,26 @@ setNonEnumerableReadOnly( REPL.prototype, 'close', function close() { * @private */ function onTick() { + var key; + var o; + var i; + var j; + debug( 'Closing readline interface...' ); self._rli.close(); + + // If this is a non-sandboxed REPL, remove global variables/properties which were introduced during context creation... + if ( self._sandbox === false ) { + for ( i = 0; i < self._globalVars.length; i++ ) { + o = self._context; + key = self._globalVars[ i ].split( '.' ); // Note: this addresses nested key paths (e.g., `a.b.c`) + for ( j = 0; j < key.length-1; j++ ) { + o = o[ key[ j ] ]; + } + delete o[ key[ j ] ]; + } + self._globalVars.length = 0; + } } }); From 83181747a4a0316cf78672229261c82aada0a1f2 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 03:20:26 -0700 Subject: [PATCH 097/142] Move functions to separate files --- .../@stdlib/repl/ctor/lib/aliases.js | 33 ++++ .../@stdlib/repl/ctor/lib/create_context.js | 156 +----------------- .../@stdlib/repl/ctor/lib/set_aliases.js | 69 ++++++++ .../repl/ctor/lib/set_aliases_global.js | 88 ++++++++++ .../@stdlib/repl/ctor/lib/set_commands.js | 55 ++++++ .../repl/ctor/lib/set_commands_global.js | 64 +++++++ 6 files changed, 313 insertions(+), 152 deletions(-) create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/aliases.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/set_commands.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/set_commands_global.js diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/aliases.js b/lib/node_modules/@stdlib/repl/ctor/lib/aliases.js new file mode 100644 index 000000000000..468b5b2528ad --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/aliases.js @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var aliases = require( '@stdlib/namespace/aliases' ); + + +// MAIN // + +var ALIASES = aliases(); // NOTE: we assume all aliases are unique (no duplicates!) + + +// EXPORTS // + +module.exports = ALIASES; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index ddbd31252557..04ec9073b060 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -27,20 +27,17 @@ var vm = require( 'vm' ); var Console = require( 'console' ).Console; var logger = require( 'debug' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; -var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var getGlobal = require( '@stdlib/utils/global' ); var objectKeys = require( '@stdlib/utils/keys' ); var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); -var setReadOnlyAccessor = require( '@stdlib/utils/define-read-only-accessor' ); var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); -var setConfigurableReadOnlyAccessor = require( '@stdlib/utils/define-configurable-read-only-accessor' ); // eslint-disable-line id-length -var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); -var aliases = require( '@stdlib/namespace/aliases' ); -var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); var createRequire = require( './create_require.js' ); -var createAccessor = require( './create_accessor.js' ); var HELP_TEXT = require( './help_text.js' ); var GLOBALS = require( './globals.js' ); +var setAliases = require( './set_aliases.js' ); +var setAliasesGlobal = require( './set_aliases_globa.js' ); +var setCommands = require( './set_commands.js' ); +var setCommandsGlobal = require( './set_commands_global.js' ); // VARIABLES // @@ -50,151 +47,6 @@ var debug = logger( 'repl:context' ); // Cache references to module methods (WARNING: use of *private* methods exposed on the `Module` object; thus, breakage is possible!): var resolveLookupPaths = Module._resolveLookupPaths; -// Cache the list of aliases: -var ALIASES = aliases(); // NOTE: we assume all aliases are unique (no duplicates!) - - -// FUNCTIONS // - -/** -* Sets commands on a sandboxed `context` object. -* -* @private -* @param {Object} context - context object -* @param {ArrayArray} commands - commands -* @returns {Object} context object -*/ -function setCommands( context, commands ) { - var cmd; - var i; - - for ( i = 0; i < commands.length; i++ ) { - cmd = commands[ i ]; - if ( cmd[ 2 ] ) { - setReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); - } else { - setReadOnly( context, cmd[ 0 ], cmd[ 1 ] ); - } - } - return context; -} - -/** -* Sets aliases on a sandboxed `context` object. -* -* @private -* @param {Object} context - context object -* @returns {Object} context object -*/ -function setAliases( context ) { - var key; - var pkg; - var o; - var i; - var j; - var k; - - // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to recursively generate nested objects... - for ( i = 0; i < ALIASES.length; i++ ) { - o = context; - key = ALIASES[ i ].split( '.' ); - for ( j = 0; j < key.length-1; j++ ) { - k = key[ j ]; - if ( !hasOwnProp( o, k ) ) { - setReadOnly( o, k, {} ); - } - o = o[ k ]; - } - k = key[ j ]; - pkg = alias2pkg( ALIASES[ i ] ); - setMemoizedReadOnly( o, k, createAccessor( context.require, pkg ) ); - } - return context; -} - -/** -* Sets commands on non-sandboxed `context` object. -* -* ## Notes -* -* - This function avoids overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects. -* -* @private -* @param {Array} out - output array for storing a list of global variables added to the global namespace -* @param {Object} context - context object -* @param {ArrayArray} commands - commands -* @returns {Object} context object -*/ -function setCommandsGlobal( out, context, commands ) { - var cmd; - var i; - - for ( i = 0; i < commands.length; i++ ) { - cmd = commands[ i ]; - if ( !hasOwnProp( context, cmd[ 0 ] ) ) { - out.push( cmd[ 0 ] ); - if ( cmd[ 2 ] ) { - setConfigurableReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); - } else { - setConfigurableReadOnly( context, cmd[ 0 ], cmd[ 1 ] ); - } - } - } - return context; -} - -/** -* Sets aliases on a non-sandboxed `context` object. -* -* ## Notes -* -* - This function avoids overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects. -* -* @private -* @param {Array} out - output array for storing a list of global variables added to the global namespace -* @param {Object} context - context object -* @returns {Object} context object -*/ -function setAliasesGlobal( out, context ) { - var key; - var FLG; - var pkg; - var o; - var i; - var j; - var k; - - // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to recursively generate nested objects... - for ( i = 0; i < ALIASES.length; i++ ) { - o = context; - FLG = false; - key = ALIASES[ i ].split( '.' ); - for ( j = 0; j < key.length-1; j++ ) { - k = key[ j ]; - if ( !hasOwnProp( o, k ) ) { - // Upon first encountering a new property, we need to remember the current key path, so that we can later remove the properties upon closing the REPL... - if ( FLG === false ) { - FLG = true; - out.push( key.slice( 0, j+1 ).join( '.' ) ); - } - setReadOnly( o, k, {} ); - } - o = o[ k ]; - } - k = key[ j ]; - - // Avoid overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects (e.g., don't break an already running application which has already defined a particular global variable)... - if ( !hasOwnProp( o, k ) ) { - if ( FLG === false ) { - out.push( ALIASES[ i ] ); - } - pkg = alias2pkg( ALIASES[ i ] ); - setMemoizedReadOnly( o, k, createAccessor( context.require, pkg ) ); - } - } - return context; -} - // MAIN // diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js new file mode 100644 index 000000000000..9fd07b599b9f --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); +var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var createAccessor = require( './create_accessor.js' ); +var ALIASES = require( './aliases.js' ); + + +// MAIN // + +/** +* Sets aliases on a sandboxed `context` object. +* +* @private +* @param {Object} context - context object +* @returns {Object} context object +*/ +function setAliases( context ) { + var key; + var pkg; + var o; + var i; + var j; + var k; + + // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to recursively generate nested objects... + for ( i = 0; i < ALIASES.length; i++ ) { + o = context; + key = ALIASES[ i ].split( '.' ); + for ( j = 0; j < key.length-1; j++ ) { + k = key[ j ]; + if ( !hasOwnProp( o, k ) ) { + setReadOnly( o, k, {} ); + } + o = o[ k ]; + } + k = key[ j ]; + pkg = alias2pkg( ALIASES[ i ] ); + setMemoizedReadOnly( o, k, createAccessor( context.require, pkg ) ); + } + return context; +} + + +// EXPORTS // + +module.exports = setAliases; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js new file mode 100644 index 000000000000..6c8386befe58 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js @@ -0,0 +1,88 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); +var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var createAccessor = require( './create_accessor.js' ); +var ALIASES = require( './aliases.js' ); + + +// MAIN // + +/** +* Sets aliases on a non-sandboxed `context` object. +* +* ## Notes +* +* - This function avoids overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects. +* +* @private +* @param {Array} out - output array for storing a list of global variables added to the global namespace +* @param {Object} context - context object +* @returns {Object} context object +*/ +function setAliasesGlobal( out, context ) { + var key; + var FLG; + var pkg; + var o; + var i; + var j; + var k; + + // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to recursively generate nested objects... + for ( i = 0; i < ALIASES.length; i++ ) { + o = context; + FLG = false; + key = ALIASES[ i ].split( '.' ); + for ( j = 0; j < key.length-1; j++ ) { + k = key[ j ]; + if ( !hasOwnProp( o, k ) ) { + // Upon first encountering a new property, we need to remember the current key path, so that we can later remove the properties upon closing the REPL... + if ( FLG === false ) { + FLG = true; + out.push( key.slice( 0, j+1 ).join( '.' ) ); + } + setReadOnly( o, k, {} ); + } + o = o[ k ]; + } + k = key[ j ]; + + // Avoid overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects (e.g., don't break an already running application which has already defined a particular global variable)... + if ( !hasOwnProp( o, k ) ) { + if ( FLG === false ) { + out.push( ALIASES[ i ] ); + } + pkg = alias2pkg( ALIASES[ i ] ); + setMemoizedReadOnly( o, k, createAccessor( context.require, pkg ) ); + } + } + return context; +} + + +// EXPORTS // + +module.exports = setAliasesGlobal; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_commands.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_commands.js new file mode 100644 index 000000000000..ff01369ddfd3 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_commands.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); +var setReadOnlyAccessor = require( '@stdlib/utils/define-read-only-accessor' ); + + +// MAIN // + +/** +* Sets commands on a sandboxed `context` object. +* +* @private +* @param {Object} context - context object +* @param {ArrayArray} commands - commands +* @returns {Object} context object +*/ +function setCommands( context, commands ) { + var cmd; + var i; + + for ( i = 0; i < commands.length; i++ ) { + cmd = commands[ i ]; + if ( cmd[ 2 ] ) { + setReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); + } else { + setReadOnly( context, cmd[ 0 ], cmd[ 1 ] ); + } + } + return context; +} + + +// EXPORTS // + +module.exports = setCommands; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_commands_global.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_commands_global.js new file mode 100644 index 000000000000..044dfb663cca --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_commands_global.js @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); +var setConfigurableReadOnlyAccessor = require( '@stdlib/utils/define-configurable-read-only-accessor' ); // eslint-disable-line id-length + + +// MAIN // + +/** +* Sets commands on non-sandboxed `context` object. +* +* ## Notes +* +* - This function avoids overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects. +* +* @private +* @param {Array} out - output array for storing a list of global variables added to the global namespace +* @param {Object} context - context object +* @param {ArrayArray} commands - commands +* @returns {Object} context object +*/ +function setCommandsGlobal( out, context, commands ) { + var cmd; + var i; + + for ( i = 0; i < commands.length; i++ ) { + cmd = commands[ i ]; + if ( !hasOwnProp( context, cmd[ 0 ] ) ) { + out.push( cmd[ 0 ] ); + if ( cmd[ 2 ] ) { + setConfigurableReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); + } else { + setConfigurableReadOnly( context, cmd[ 0 ], cmd[ 1 ] ); + } + } + } + return context; +} + + +// EXPORTS // + +module.exports = setCommandsGlobal; From 82246b29b8691fcb4923e49aedf9ef09e9f86c08 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 03:25:51 -0700 Subject: [PATCH 098/142] Add debug statements --- .../@stdlib/repl/ctor/lib/set_aliases_global.js | 10 +++++++++- .../@stdlib/repl/ctor/lib/set_commands_global.js | 10 +++++++++- 2 files changed, 18 insertions(+), 2 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js index 6c8386befe58..e2484e480a30 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js @@ -20,6 +20,7 @@ // MODULES // +var logger = require( 'debug' ); var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); @@ -28,6 +29,11 @@ var createAccessor = require( './create_accessor.js' ); var ALIASES = require( './aliases.js' ); +// VARIABLES // + +var debug = logger( 'repl:set_aliases' ); + + // MAIN // /** @@ -71,7 +77,9 @@ function setAliasesGlobal( out, context ) { k = key[ j ]; // Avoid overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects (e.g., don't break an already running application which has already defined a particular global variable)... - if ( !hasOwnProp( o, k ) ) { + if ( hasOwnProp( o, k ) ) { + debug( 'Skipping alias as global context property `'+ALIASES[i]+'` is already assigned.' ); + } else { if ( FLG === false ) { out.push( ALIASES[ i ] ); } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_commands_global.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_commands_global.js index 044dfb663cca..04d61b0a0d4c 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_commands_global.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_commands_global.js @@ -20,11 +20,17 @@ // MODULES // +var logger = require( 'debug' ); var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); var setConfigurableReadOnlyAccessor = require( '@stdlib/utils/define-configurable-read-only-accessor' ); // eslint-disable-line id-length +// VARIABLES // + +var debug = logger( 'repl:set_commands' ); + + // MAIN // /** @@ -46,7 +52,9 @@ function setCommandsGlobal( out, context, commands ) { for ( i = 0; i < commands.length; i++ ) { cmd = commands[ i ]; - if ( !hasOwnProp( context, cmd[ 0 ] ) ) { + if ( hasOwnProp( context, cmd[ 0 ] ) ) { + debug( 'Skipping command as global context property `'+cmd[0]+'` is already assigned.' ); + } else { out.push( cmd[ 0 ] ); if ( cmd[ 2 ] ) { setConfigurableReadOnlyAccessor( context, cmd[ 0 ], cmd[ 1 ] ); From ba0f85c75324b72836523e88a8b31f9c0a807ded Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 03:26:54 -0700 Subject: [PATCH 099/142] Fix require path --- lib/node_modules/@stdlib/repl/ctor/lib/create_context.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 04ec9073b060..88bf15ee74a3 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -35,7 +35,7 @@ var createRequire = require( './create_require.js' ); var HELP_TEXT = require( './help_text.js' ); var GLOBALS = require( './globals.js' ); var setAliases = require( './set_aliases.js' ); -var setAliasesGlobal = require( './set_aliases_globa.js' ); +var setAliasesGlobal = require( './set_aliases_global.js' ); var setCommands = require( './set_commands.js' ); var setCommandsGlobal = require( './set_commands_global.js' ); From 8b0bb1e277ef7f63406e415ed1f6574dc9404506 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 03:31:10 -0700 Subject: [PATCH 100/142] Fix copyright year --- lib/node_modules/@stdlib/repl/ctor/examples/index.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/examples/index.js b/lib/node_modules/@stdlib/repl/ctor/examples/index.js index 77f6319f7514..992da19e6295 100644 --- a/lib/node_modules/@stdlib/repl/ctor/examples/index.js +++ b/lib/node_modules/@stdlib/repl/ctor/examples/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. From 5d36d03c9854efa1cceda00ea35987b153be2c2e Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 03:33:04 -0700 Subject: [PATCH 101/142] Update comment --- lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js index e2484e480a30..85b345420ff0 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js @@ -57,7 +57,7 @@ function setAliasesGlobal( out, context ) { var j; var k; - // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to recursively generate nested objects... + // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to generate nested objects... for ( i = 0; i < ALIASES.length; i++ ) { o = context; FLG = false; From 84a73b97fb22f7b12990e2dac090594bd6a79220 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 12:12:25 -0700 Subject: [PATCH 102/142] Refactor to provide the context object as an argument --- lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js | 6 +++--- lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js | 2 +- .../@stdlib/repl/ctor/lib/set_aliases_global.js | 2 +- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js index 6fcfbb8a9edf..74c45f09e968 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js @@ -24,11 +24,11 @@ * Returns an accessor for loading an underlying implementation upon first access. * * @private -* @param {Function} require - context `require` function +* @param {Object} context - context object * @param {string} pkg - package name * @returns {Function} get accessor */ -function createAccessor( require, pkg ) { +function createAccessor( context, pkg ) { return get; /** @@ -38,7 +38,7 @@ function createAccessor( require, pkg ) { * @returns {*} package export */ function get() { - return require( pkg ); // eslint-disable-line stdlib/no-dynamic-require + return context.require( pkg ); } } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js index 9fd07b599b9f..0d533c27447e 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js @@ -58,7 +58,7 @@ function setAliases( context ) { } k = key[ j ]; pkg = alias2pkg( ALIASES[ i ] ); - setMemoizedReadOnly( o, k, createAccessor( context.require, pkg ) ); + setMemoizedReadOnly( o, k, createAccessor( context, pkg ) ); } return context; } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js index 85b345420ff0..0f617f38355e 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js @@ -84,7 +84,7 @@ function setAliasesGlobal( out, context ) { out.push( ALIASES[ i ] ); } pkg = alias2pkg( ALIASES[ i ] ); - setMemoizedReadOnly( o, k, createAccessor( context.require, pkg ) ); + setMemoizedReadOnly( o, k, createAccessor( context, pkg ) ); } } return context; From b4e04ad239a3ca89a2b59ef969139115d357a0e2 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 12:23:01 -0700 Subject: [PATCH 103/142] Cache resolved global variables/properties --- .../@stdlib/repl/ctor/lib/create_accessor.js | 13 ++++++++++--- lib/node_modules/@stdlib/repl/ctor/lib/main.js | 5 ++++- .../@stdlib/repl/ctor/lib/set_aliases.js | 9 ++++----- .../@stdlib/repl/ctor/lib/set_aliases_global.js | 13 ++++++------- 4 files changed, 24 insertions(+), 16 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js index 74c45f09e968..99a923676884 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js @@ -18,6 +18,11 @@ 'use strict'; +// MODULES // + +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); + + // MAIN // /** @@ -25,10 +30,10 @@ * * @private * @param {Object} context - context object -* @param {string} pkg - package name +* @param {string} alias - alias * @returns {Function} get accessor */ -function createAccessor( context, pkg ) { +function createAccessor( context, alias ) { return get; /** @@ -38,7 +43,9 @@ function createAccessor( context, pkg ) { * @returns {*} package export */ function get() { - return context.require( pkg ); + var v = context.require( alias2pkg( alias ) ); + context._aliases.push( [ alias, v ] ); // eslint-disable-line no-underscore-dangle + return v; } } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index b986dd24eb2c..84a4fbdaef6a 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -125,9 +125,12 @@ function REPL( options ) { // Initialize an internal buffer for saving regular expression matches between command evaluations: setNonEnumerableReadOnly( this, '_regexp', [ '', '', '', '', '', '', '', '', '', '' ] ); - // For non-sandboxed REPLs, initialize an internal buffer for storing a list of global variables which need to be deleted upon closing a REPL in order to allow garbage collection and prevent memory leaks: + // For non-sandboxed REPLs, initialize an internal buffer for storing a list of global variables/properties which need to be deleted upon closing a REPL in order to allow garbage collection and prevent memory leaks: setNonEnumerableReadOnly( this, '_globalVars', ( this._sandbox ) ? null : [] ); + // Initialize an internal cache of resolved global variables/properties in order to allow, e.g., help text look-up based on object reference, not just alias name (note: members are of the form `[ '', ]`: + setNonEnumerableReadOnly( this, '_aliases', [] ); + // Initialize an internal flag indicating whether the REPL has been closed: setNonEnumerable( this, '_closed', false ); diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js index 0d533c27447e..2d36fc48a7e3 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js @@ -23,7 +23,6 @@ var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); -var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); var createAccessor = require( './create_accessor.js' ); var ALIASES = require( './aliases.js' ); @@ -38,8 +37,8 @@ var ALIASES = require( './aliases.js' ); * @returns {Object} context object */ function setAliases( context ) { + var alias; var key; - var pkg; var o; var i; var j; @@ -48,7 +47,8 @@ function setAliases( context ) { // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to recursively generate nested objects... for ( i = 0; i < ALIASES.length; i++ ) { o = context; - key = ALIASES[ i ].split( '.' ); + alias = ALIASES[ i ]; + key = alias.split( '.' ); for ( j = 0; j < key.length-1; j++ ) { k = key[ j ]; if ( !hasOwnProp( o, k ) ) { @@ -57,8 +57,7 @@ function setAliases( context ) { o = o[ k ]; } k = key[ j ]; - pkg = alias2pkg( ALIASES[ i ] ); - setMemoizedReadOnly( o, k, createAccessor( context, pkg ) ); + setMemoizedReadOnly( o, k, createAccessor( context, alias ) ); } return context; } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js index 0f617f38355e..f1c776cb6518 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js @@ -24,7 +24,6 @@ var logger = require( 'debug' ); var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); -var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); var createAccessor = require( './create_accessor.js' ); var ALIASES = require( './aliases.js' ); @@ -49,9 +48,9 @@ var debug = logger( 'repl:set_aliases' ); * @returns {Object} context object */ function setAliasesGlobal( out, context ) { + var alias; var key; var FLG; - var pkg; var o; var i; var j; @@ -60,8 +59,9 @@ function setAliasesGlobal( out, context ) { // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to generate nested objects... for ( i = 0; i < ALIASES.length; i++ ) { o = context; + alias = ALIASES[ i ]; FLG = false; - key = ALIASES[ i ].split( '.' ); + key = alias.split( '.' ); for ( j = 0; j < key.length-1; j++ ) { k = key[ j ]; if ( !hasOwnProp( o, k ) ) { @@ -78,13 +78,12 @@ function setAliasesGlobal( out, context ) { // Avoid overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects (e.g., don't break an already running application which has already defined a particular global variable)... if ( hasOwnProp( o, k ) ) { - debug( 'Skipping alias as global context property `'+ALIASES[i]+'` is already assigned.' ); + debug( 'Skipping alias as global context property `'+alias+'` is already assigned.' ); } else { if ( FLG === false ) { - out.push( ALIASES[ i ] ); + out.push( alias ); } - pkg = alias2pkg( ALIASES[ i ] ); - setMemoizedReadOnly( o, k, createAccessor( context, pkg ) ); + setMemoizedReadOnly( o, k, createAccessor( context, alias ) ); } } return context; From c4c512ff0d57670d5fb62ead6d3e298b55bf72fe Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 12:25:09 -0700 Subject: [PATCH 104/142] Convert internal buffer to a strided array --- lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js | 2 +- lib/node_modules/@stdlib/repl/ctor/lib/main.js | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js index 99a923676884..9278a00aec1e 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js @@ -44,7 +44,7 @@ function createAccessor( context, alias ) { */ function get() { var v = context.require( alias2pkg( alias ) ); - context._aliases.push( [ alias, v ] ); // eslint-disable-line no-underscore-dangle + context._aliases.push( alias, v ); // eslint-disable-line no-underscore-dangle return v; } } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index 84a4fbdaef6a..56915cbb96c7 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -128,7 +128,7 @@ function REPL( options ) { // For non-sandboxed REPLs, initialize an internal buffer for storing a list of global variables/properties which need to be deleted upon closing a REPL in order to allow garbage collection and prevent memory leaks: setNonEnumerableReadOnly( this, '_globalVars', ( this._sandbox ) ? null : [] ); - // Initialize an internal cache of resolved global variables/properties in order to allow, e.g., help text look-up based on object reference, not just alias name (note: members are of the form `[ '', ]`: + // Initialize a strided internal cache of resolved global variables/properties in order to allow, e.g., help text look-up based on object reference, not just alias name (note: members alternate between `''` and ``): setNonEnumerableReadOnly( this, '_aliases', [] ); // Initialize an internal flag indicating whether the REPL has been closed: From c6f9e65dc57d3629c6a7ac1bcd8408c32f13ccfc Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 14:21:44 -0700 Subject: [PATCH 105/142] Add support for resolving a package name based on an object reference --- .../@stdlib/repl/ctor/lib/contains.js | 60 +++++++++++++++++++ .../@stdlib/repl/ctor/lib/create_context.js | 45 +++++++++++++- .../@stdlib/repl/ctor/lib/index_of.js | 60 +++++++++++++++++++ .../@stdlib/repl/ctor/lib/set_aliases.js | 12 +++- .../repl/ctor/lib/set_aliases_global.js | 12 +++- 5 files changed, 183 insertions(+), 6 deletions(-) create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/contains.js create mode 100644 lib/node_modules/@stdlib/repl/ctor/lib/index_of.js diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/contains.js b/lib/node_modules/@stdlib/repl/ctor/lib/contains.js new file mode 100644 index 000000000000..c525a07d7d24 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/contains.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns a boolean indicating if a strided array-like object contains a provided value. +* +* @private +* @param {NonNegativeInteger} N - number of elements to search +* @param {ArrayLike} arr - array to search +* @param {integer} stride - index stride +* @param {NonNegativeInteger} offset - index offset +* @param {*} value - search value +* @returns {boolean} boolean indicating if an array-like object contains a provided value +* +* @example +* var arr = [ 1, 2, 3 ]; +* +* var bool = contains( arr.length, arr, 1, 0, 2 ); +* // returns true +* +* bool = contains( arr.length, arr, 1, 0, 4 ); +* // returns false +*/ +function contains( N, arr, stride, offset, value ) { + var idx; + var i; + + idx = offset; + for ( i = 0; i < N; i++ ) { + if ( arr[ idx ] === value ) { + return true; + } + idx += stride; + } + return false; +} + + +// EXPORTS // + +module.exports = contains; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 88bf15ee74a3..e935c6b0b146 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -31,6 +31,8 @@ var getGlobal = require( '@stdlib/utils/global' ); var objectKeys = require( '@stdlib/utils/keys' ); var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var indexOf = require( './index_of.js' ); var createRequire = require( './create_require.js' ); var HELP_TEXT = require( './help_text.js' ); var GLOBALS = require( './globals.js' ); @@ -47,6 +49,12 @@ var debug = logger( 'repl:context' ); // Cache references to module methods (WARNING: use of *private* methods exposed on the `Module` object; thus, breakage is possible!): var resolveLookupPaths = Module._resolveLookupPaths; +// List project aliases which are overridden/wrapped to provide behavior tailored to the REPL environment: +var OVERRIDES = [ + 'alias2pkg', + 'alias2related' +]; + // MAIN // @@ -100,14 +108,15 @@ function createContext( repl ) { // Add project APIs... if ( repl._sandbox ) { - setAliases( context ); + setAliases( context, OVERRIDES ); } else { - setAliasesGlobal( repl._globalVars, context ); + setAliasesGlobal( repl._globalVars, context, OVERRIDES ); } // Define a list of REPL-specific commands (NOTE: keep in alphabetical order): cmds = [ // [ , , ] + [ 'alias2pkg', onAlias2Pkg, false ], [ 'ans', onAns, true ], [ 'clear', onClear, false ], [ 'help', onHelp, false ], @@ -149,6 +158,38 @@ function createContext( repl ) { } return context; + /** + * Returns the package name corresponding to a provided alias. + * + * @private + * @param {*} alias - alias + * @returns {string} package name + */ + function onAlias2Pkg( alias ) { + var aliases; + var pkg; + var N; + var i; + + aliases = repl._aliases; + N = aliases.length; + + if ( isString( alias ) ) { + pkg = alias2pkg( alias ); + } + // If provided an `alias` which is not a string or we failed to resolve a package name based on the provided string value, we try to resolve a string alias (and subsequently a corresponding package name) by searching the list of cached references of global variables/properties... + if ( !pkg ) { + i = indexOf( N/2, aliases, 1, 1, alias ); + if ( i >= 0 ) { + pkg = alias2pkg( aliases[ i-1 ] ); + } + } + if ( pkg ) { + return pkg; + } + return 'Error: unrecognized alias.'; + } + /** * Returns the result of the last successfully executed command. * diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/index_of.js b/lib/node_modules/@stdlib/repl/ctor/lib/index_of.js new file mode 100644 index 000000000000..5dce20f09d70 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/ctor/lib/index_of.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Searches a strided array-like object for a search value. +* +* @private +* @param {NonNegativeInteger} N - number of elements to search +* @param {ArrayLike} arr - array to search +* @param {integer} stride - index stride +* @param {NonNegativeInteger} offset - index offset +* @param {*} value - search value +* @returns {integer} search value index +* +* @example +* var arr = [ 1, 2, 3 ]; +* +* var bool = indexOf( arr.length, arr, 1, 0, 2 ); +* // returns 1 +* +* bool = indexOf( arr.length, arr, 1, 0, 4 ); +* // returns -1 +*/ +function indexOf( N, arr, stride, offset, value ) { + var idx; + var i; + + idx = offset; + for ( i = 0; i < N; i++ ) { + if ( arr[ idx ] === value ) { + return idx; + } + idx += stride; + } + return -1; +} + + +// EXPORTS // + +module.exports = indexOf; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js index 2d36fc48a7e3..69b57c81fe6c 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js @@ -23,6 +23,7 @@ var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); +var contains = require( './contains.js' ); var createAccessor = require( './create_accessor.js' ); var ALIASES = require( './aliases.js' ); @@ -34,20 +35,27 @@ var ALIASES = require( './aliases.js' ); * * @private * @param {Object} context - context object +* @param {Array} skip - list of aliases to skip * @returns {Object} context object */ -function setAliases( context ) { +function setAliases( context, skip ) { var alias; var key; + var N; var o; var i; var j; var k; + N = skip.length; + // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to recursively generate nested objects... for ( i = 0; i < ALIASES.length; i++ ) { - o = context; alias = ALIASES[ i ]; + if ( contains( N, skip, 1, 0, alias ) ) { + continue; + } + o = context; key = alias.split( '.' ); for ( j = 0; j < key.length-1; j++ ) { k = key[ j ]; diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js index f1c776cb6518..5d9c41e8386b 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js @@ -24,6 +24,7 @@ var logger = require( 'debug' ); var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); var setMemoizedReadOnly = require( '@stdlib/utils/define-memoized-read-only-property' ); +var contains = require( './contains.js' ); var createAccessor = require( './create_accessor.js' ); var ALIASES = require( './aliases.js' ); @@ -45,21 +46,28 @@ var debug = logger( 'repl:set_aliases' ); * @private * @param {Array} out - output array for storing a list of global variables added to the global namespace * @param {Object} context - context object +* @param {Array} skip - list of aliases to skip * @returns {Object} context object */ -function setAliasesGlobal( out, context ) { +function setAliasesGlobal( out, context, skip ) { var alias; var key; var FLG; + var N; var o; var i; var j; var k; + N = skip.length; + // Extend the context object, keeping in mind that an alias may be nested (e.g., `a.b.c`), and, if so, we need to generate nested objects... for ( i = 0; i < ALIASES.length; i++ ) { - o = context; alias = ALIASES[ i ]; + if ( contains( N, skip, 1, 0, alias ) ) { + continue; + } + o = context; FLG = false; key = alias.split( '.' ); for ( j = 0; j < key.length-1; j++ ) { From b95d53746db702cd73c110eb1d71e06f46105d16 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 14:28:06 -0700 Subject: [PATCH 106/142] Add support for resolving related aliases provided an object reference --- .../@stdlib/repl/ctor/lib/create_context.js | 37 ++++++++++++++++--- 1 file changed, 32 insertions(+), 5 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index e935c6b0b146..aa1306242b0e 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -32,6 +32,7 @@ var objectKeys = require( '@stdlib/utils/keys' ); var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var alias2related = require( '@stdlib/namespace/alias2related' ); var indexOf = require( './index_of.js' ); var createRequire = require( './create_require.js' ); var HELP_TEXT = require( './help_text.js' ); @@ -117,6 +118,7 @@ function createContext( repl ) { cmds = [ // [ , , ] [ 'alias2pkg', onAlias2Pkg, false ], + [ 'alias2related', onAlias2Related, false ], [ 'ans', onAns, true ], [ 'clear', onClear, false ], [ 'help', onHelp, false ], @@ -124,10 +126,6 @@ function createContext( repl ) { [ 'quit', onQuit, false ] ]; - // TODO: add `alias2pkg` command wrapper - - // TODO: add `alias2related` command wrapper - // TODO: add `example` command // TODO: add `isKeyword` command @@ -179,7 +177,7 @@ function createContext( repl ) { } // If provided an `alias` which is not a string or we failed to resolve a package name based on the provided string value, we try to resolve a string alias (and subsequently a corresponding package name) by searching the list of cached references of global variables/properties... if ( !pkg ) { - i = indexOf( N/2, aliases, 1, 1, alias ); + i = indexOf( N/2, aliases, 2, 1, alias ); if ( i >= 0 ) { pkg = alias2pkg( aliases[ i-1 ] ); } @@ -190,6 +188,35 @@ function createContext( repl ) { return 'Error: unrecognized alias.'; } + /** + * Returns aliases related to a provided alias. + * + * @private + * @param {*} alias - alias + * @returns {(string|void)} related packages as a newline-delimited list + */ + function onAlias2Related( alias ) { + var aliases; + var out; + var N; + var i; + + aliases = repl._aliases; + N = aliases.length; + + if ( isString( alias ) ) { + out = alias2related( alias ); + } + // If provided an `alias` which is not a string or we failed to resolve related aliases based on the provided string value, we try to resolve a string alias (and subsequently related aliases) by searching the list of cached references of global variables/properties... + if ( !out ) { + i = indexOf( N/2, aliases, 2, 1, alias ); + if ( i >= 0 ) { + out = alias2related( aliases[ i-1 ] ); + } + } + return ( out ) ? out.join( '\n' ) : void 0; + } + /** * Returns the result of the last successfully executed command. * From c720bd29a99dc16de46f8ae537c1b0c62501e82b Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 14:42:30 -0700 Subject: [PATCH 107/142] Fix caching --- .../@stdlib/repl/ctor/lib/create_accessor.js | 9 +++++---- .../@stdlib/repl/ctor/lib/create_context.js | 10 ++++++---- lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js | 5 +++-- .../@stdlib/repl/ctor/lib/set_aliases_global.js | 11 ++++++----- 4 files changed, 20 insertions(+), 15 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js index 9278a00aec1e..cf8b9323da6c 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_accessor.js @@ -29,11 +29,12 @@ var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); * Returns an accessor for loading an underlying implementation upon first access. * * @private -* @param {Object} context - context object +* @param {Array} out - cache for storing resolved module exports +* @param {Function} require - module loader * @param {string} alias - alias * @returns {Function} get accessor */ -function createAccessor( context, alias ) { +function createAccessor( out, require, alias ) { return get; /** @@ -43,8 +44,8 @@ function createAccessor( context, alias ) { * @returns {*} package export */ function get() { - var v = context.require( alias2pkg( alias ) ); - context._aliases.push( alias, v ); // eslint-disable-line no-underscore-dangle + var v = require( alias2pkg( alias ) ); // eslint-disable-line stdlib/no-dynamic-require + out.push( alias, v ); return v; } } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index aa1306242b0e..70e4de539588 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -109,9 +109,9 @@ function createContext( repl ) { // Add project APIs... if ( repl._sandbox ) { - setAliases( context, OVERRIDES ); + setAliases( repl._aliases, context, OVERRIDES ); } else { - setAliasesGlobal( repl._globalVars, context, OVERRIDES ); + setAliasesGlobal( repl._globalVars, repl._aliases, context, OVERRIDES ); } // Define a list of REPL-specific commands (NOTE: keep in alphabetical order): @@ -193,7 +193,7 @@ function createContext( repl ) { * * @private * @param {*} alias - alias - * @returns {(string|void)} related packages as a newline-delimited list + * @returns {(StringArray|void)} related packages as a newline-delimited list */ function onAlias2Related( alias ) { var aliases; @@ -214,7 +214,9 @@ function createContext( repl ) { out = alias2related( aliases[ i-1 ] ); } } - return ( out ) ? out.join( '\n' ) : void 0; + if ( out && out.length ) { + return out; + } } /** diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js index 69b57c81fe6c..c67e86dfd394 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases.js @@ -34,11 +34,12 @@ var ALIASES = require( './aliases.js' ); * Sets aliases on a sandboxed `context` object. * * @private +* @param {Array} out - strided output array for storing resolved module exports * @param {Object} context - context object * @param {Array} skip - list of aliases to skip * @returns {Object} context object */ -function setAliases( context, skip ) { +function setAliases( out, context, skip ) { var alias; var key; var N; @@ -65,7 +66,7 @@ function setAliases( context, skip ) { o = o[ k ]; } k = key[ j ]; - setMemoizedReadOnly( o, k, createAccessor( context, alias ) ); + setMemoizedReadOnly( o, k, createAccessor( out, context.require, alias ) ); // eslint-disable-line max-len } return context; } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js index 5d9c41e8386b..259f56c0db9a 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/set_aliases_global.js @@ -44,12 +44,13 @@ var debug = logger( 'repl:set_aliases' ); * - This function avoids overwriting properties in a non-sandboxed environment in order to avoid unintended side-effects. * * @private -* @param {Array} out - output array for storing a list of global variables added to the global namespace +* @param {Array} out1 - output array for storing a list of global variables added to the global namespace +* @param {Array} out2 - strided output array for storing resolved module exports * @param {Object} context - context object * @param {Array} skip - list of aliases to skip * @returns {Object} context object */ -function setAliasesGlobal( out, context, skip ) { +function setAliasesGlobal( out1, out2, context, skip ) { var alias; var key; var FLG; @@ -76,7 +77,7 @@ function setAliasesGlobal( out, context, skip ) { // Upon first encountering a new property, we need to remember the current key path, so that we can later remove the properties upon closing the REPL... if ( FLG === false ) { FLG = true; - out.push( key.slice( 0, j+1 ).join( '.' ) ); + out1.push( key.slice( 0, j+1 ).join( '.' ) ); } setReadOnly( o, k, {} ); } @@ -89,9 +90,9 @@ function setAliasesGlobal( out, context, skip ) { debug( 'Skipping alias as global context property `'+alias+'` is already assigned.' ); } else { if ( FLG === false ) { - out.push( alias ); + out1.push( alias ); } - setMemoizedReadOnly( o, k, createAccessor( context, alias ) ); + setMemoizedReadOnly( o, k, createAccessor( out2, context.require, alias ) ); // eslint-disable-line max-len } } return context; From d65ab57d0a463a4f1ba34357c087e382f8e22d7e Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 14:47:16 -0700 Subject: [PATCH 108/142] Print error message if unrelated to resolve related --- .../@stdlib/repl/ctor/lib/create_context.js | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 70e4de539588..34dcd1d173c8 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -161,7 +161,7 @@ function createContext( repl ) { * * @private * @param {*} alias - alias - * @returns {string} package name + * @returns {(string|void)} package name */ function onAlias2Pkg( alias ) { var aliases; @@ -185,7 +185,7 @@ function createContext( repl ) { if ( pkg ) { return pkg; } - return 'Error: unrecognized alias.'; + console.error( 'Error: unrecognized alias.' ); // eslint-disable-line no-console } /** @@ -214,7 +214,11 @@ function createContext( repl ) { out = alias2related( aliases[ i-1 ] ); } } - if ( out && out.length ) { + if ( out === void 0 || out === null ) { + console.error( 'Error: unrecognized alias.' ); // eslint-disable-line no-console + return; + } + if ( out.length ) { return out; } } From 9749db16003c541c31a75d4228a8eec3025771fb Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 18:37:12 -0700 Subject: [PATCH 109/142] Refactor database generation and package API --- lib/node_modules/@stdlib/repl/help/LICENSE | 356 +++ lib/node_modules/@stdlib/repl/help/README.md | 103 +- .../@stdlib/repl/help/benchmark/benchmark.js | 21 +- lib/node_modules/@stdlib/repl/help/bin/cli | 64 + .../@stdlib/repl/help/data/data.csv | 1886 ++++++++++++++++ .../@stdlib/repl/help/data/data.json | 1 + .../@stdlib/repl/help/datapackage.json | 60 + .../@stdlib/repl/help/docs/repl.txt | 21 + .../@stdlib/repl/help/docs/types/index.d.ts | 35 + .../@stdlib/repl/help/docs/types/test.ts | 44 + .../@stdlib/repl/help/docs/usage.txt | 8 + .../@stdlib/repl/help/etc/cli_opts.json | 15 + .../@stdlib/repl/help/examples/index.js | 19 +- lib/node_modules/@stdlib/repl/help/lib/db.js | 1915 ----------------- .../@stdlib/repl/help/lib/index.js | 6 +- .../@stdlib/repl/help/lib/main.js | 27 +- .../@stdlib/repl/help/package.json | 8 +- .../@stdlib/repl/help/scripts/build.js | 116 +- .../@stdlib/repl/help/test/test.cli.js | 184 ++ .../@stdlib/repl/help/test/test.js | 65 +- 20 files changed, 2921 insertions(+), 2033 deletions(-) create mode 100644 lib/node_modules/@stdlib/repl/help/LICENSE create mode 100755 lib/node_modules/@stdlib/repl/help/bin/cli create mode 100644 lib/node_modules/@stdlib/repl/help/data/data.csv create mode 100644 lib/node_modules/@stdlib/repl/help/data/data.json create mode 100644 lib/node_modules/@stdlib/repl/help/datapackage.json create mode 100644 lib/node_modules/@stdlib/repl/help/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/repl/help/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/repl/help/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/repl/help/docs/usage.txt create mode 100644 lib/node_modules/@stdlib/repl/help/etc/cli_opts.json delete mode 100644 lib/node_modules/@stdlib/repl/help/lib/db.js create mode 100644 lib/node_modules/@stdlib/repl/help/test/test.cli.js diff --git a/lib/node_modules/@stdlib/repl/help/LICENSE b/lib/node_modules/@stdlib/repl/help/LICENSE new file mode 100644 index 000000000000..dc6d53e33997 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/LICENSE @@ -0,0 +1,356 @@ +The use of the database is licensed under an Open Data Commons Public Domain +Dedication & License 1.0 (PDDL 1.0), while the database contents are licensed +under Creative Commons Zero v1.0 Universal (CC0 1.0). 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Some jurisdictions do not allow the exclusion of implied warranties, so this exclusion may not apply to You. + +5.2 Subject to any liability that may not be excluded or limited by law, the Rightsholder is not liable for, and expressly excludes, all liability for loss or damage however and whenever caused to anyone by any use under this Document, whether by You or by anyone else, and whether caused by any fault on the part of the Rightsholder or not. This exclusion of liability includes, but is not limited to, any special, incidental, consequential, punitive, or exemplary damages. This exclusion applies even if the Rightsholder has been advised of the possibility of such damages. + +5.3 If liability may not be excluded by law, it is limited to actual and direct financial loss to the extent it is caused by proved negligence on the part of the Rightsholder. + +6.0 General + +6.1 If any provision of this Document is held to be invalid or unenforceable, that must not affect the validity or enforceability of the remainder of the terms of this Document. + +6.2 This Document is the entire agreement between the parties with respect to the Work covered here. It replaces any earlier understandings, agreements or representations with respect to the Work not specified here. + +6.3 This Document does not affect any rights that You or anyone else may independently have under any applicable law to make any use of this Work, including (for jurisdictions where this Document is a licence) fair dealing, fair use, database exceptions, or any other legally recognised limitation or exception to infringement of copyright or other applicable laws. + +6.4 This Document takes effect in the relevant jurisdiction in which the Document terms are sought to be enforced. If the rights waived or granted under applicable law in the relevant jurisdiction includes additional rights not waived or granted under this Document, these additional rights are included in this Document in order to meet the intent of this Document. diff --git a/lib/node_modules/@stdlib/repl/help/README.md b/lib/node_modules/@stdlib/repl/help/README.md index 73c8d03a89b9..62158e8228c2 100644 --- a/lib/node_modules/@stdlib/repl/help/README.md +++ b/lib/node_modules/@stdlib/repl/help/README.md @@ -2,7 +2,7 @@ @license Apache-2.0 -Copyright (c) 2018 The Stdlib Authors. +Copyright (c) 2019 The Stdlib Authors. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -20,7 +20,7 @@ limitations under the License. # Help -> REPL help texts. +> Return help text associated with a provided alias. @@ -40,13 +40,20 @@ limitations under the License. var help = require( '@stdlib/repl/help' ); ``` -#### help() +#### help( alias ) -Returns an `object` containing REPL help texts. +Returns help text for a provided alias. ```javascript -var o = help(); -// returns {...} +var txt = help( 'base.sin' ); +// returns +``` + +If provided an unrecognized `alias`, the function returns `null`. + +```javascript +var txt = help( 'unrecognized_alias_beep_boop_bop_bip' ); +// returns null ``` @@ -72,17 +79,81 @@ var o = help(); ```javascript +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); var help = require( '@stdlib/repl/help' ); -var o = help(); -console.log( o ); -// => {...} +var list; +var len; +var idx; +var i; + +list = aliases(); +len = list.length; + +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len-1 ); + console.log( help( list[ idx ] ) ); +} ``` + + +* * * + +
+ +## CLI + + + +
+ +### Usage + +```text +Usage: stdlib-help-text [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```bash +$ stdlib-help-text 'base.sin' +``` + +
+ + + +
+ + +
@@ -91,10 +162,24 @@ console.log( o ); + + +## License + +The data files (databases) are licensed under an [Open Data Commons Public Domain Dedication & License 1.0][pddl-1.0] and their contents are licensed under [Creative Commons Zero v1.0 Universal][cc0]. The software is licensed under [Apache License, Version 2.0][apache-license]. + + +
+[pddl-1.0]: http://opendatacommons.org/licenses/pddl/1.0/ + +[cc0]: https://creativecommons.org/publicdomain/zero/1.0 + +[apache-license]: https://www.apache.org/licenses/LICENSE-2.0 +
diff --git a/lib/node_modules/@stdlib/repl/help/benchmark/benchmark.js b/lib/node_modules/@stdlib/repl/help/benchmark/benchmark.js index f7df0f6871c0..3461d4f0646b 100644 --- a/lib/node_modules/@stdlib/repl/help/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/repl/help/benchmark/benchmark.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -21,7 +21,8 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var isPlainObject = require( '@stdlib/assert/is-plain-object' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var aliases = require( '@stdlib/namespace/aliases' ); var pkg = require( './../package.json' ).name; var help = require( './../lib' ); @@ -29,18 +30,22 @@ var help = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { - var o; + var values; + var v; var i; + + values = aliases(); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - o = help(); - if ( typeof o !== 'object' ) { - b.fail( 'should return an object' ); + v = help( values[ i%values.length ] ); + if ( typeof v !== 'string' ) { + b.fail( 'should return a string' ); } } b.toc(); - if ( !isPlainObject( o ) ) { - b.fail( 'should return a plain object' ); + if ( !isString( v ) ) { + b.fail( 'should return a string' ); } b.pass( 'benchmark finished' ); b.end(); diff --git a/lib/node_modules/@stdlib/repl/help/bin/cli b/lib/node_modules/@stdlib/repl/help/bin/cli new file mode 100755 index 000000000000..be98757c1425 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/bin/cli @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var readFileSync = require( '@stdlib/fs/read-file' ).sync; +var CLI = require( '@stdlib/tools/cli' ); +var help = require( './../lib' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var args; + var cli; + var out; + + // Create a command-line interface: + cli = new CLI({ + 'pkg': require( './../package.json' ), + 'options': require( './../etc/cli_opts.json' ), + 'help': readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }) + }); + + // Get any provided command-line arguments: + args = cli.args(); + + // Print help text corresponding to a provided alias... + out = help( args[ 0 ] ); + if ( out ) { + console.log( out ); // eslint-disable-line no-console + } else { + cli.exit( 1 ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/repl/help/data/data.csv b/lib/node_modules/@stdlib/repl/help/data/data.csv new file mode 100644 index 000000000000..c45470ca30de --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/data/data.csv @@ -0,0 +1,1886 @@ +AFINN_96,"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some "words" are phrases; e.g., "cashing in", "cool stuff".\n - Words may contain apostrophes; e.g., "can't stand".\n - Words may contain dashes; e.g., "cover-up", "made-up".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. "A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs." In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n" +AFINN_111,"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., "n00b".\n - Some "words" are phrases; e.g., "cool stuff", "not good".\n - Words may contain apostrophes; e.g., "can't stand".\n - Words may contain diaeresis; e.g., "naïve".\n - Words may contain dashes; e.g., "self-deluded", "self-confident".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. "A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs." In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n" +alias2pkg,"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( '{{alias:@stdlib/math/base/special/sin}}' )\n '@stdlib/math/base/special/sin'\n\n" +alias2related,"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( '{{alias:@stdlib/math/base/special/sin}}' )\n [...]\n\n" +aliases,"\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n" +allocUnsafe,"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n" +anova1,"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n" +ANSCOMBES_QUARTET,"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. "Graphs in Statistical Analysis." *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n" +any,"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n" +anyBy,"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n" +anyByAsync,"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n" +anyByRight,"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n" +anyByRightAsync,"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n" +APERY,"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n" +append,"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n" +ARCH,"\nARCH\n Operating system CPU architecture.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n" +argumentFunction,"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n" +ARGV,"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n" +array,"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow "safe" casts.\n - 'same-kind': allow "safe" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n" +array2buffer,"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n" +array2iterator,"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n" +array2iteratorRight,"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n" +ArrayBuffer,"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n" +arraybuffer2buffer,"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new {{alias:@stdlib/array/buffer}}( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n" +arrayCtors,"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n" +arrayDataType,"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n" +arrayDataTypes,"\narrayDataTypes()\n Returns a list of array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n \n\n" +arrayMinDataType,"\narrayMinDataType( value )\n Returns the minimum array data type of the closest "kind" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n" +arrayNextDataType,"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n" +arrayPromotionRules,"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest "kind" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Array data type.\n\n dtype2: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n" +arraySafeCasts,"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n" +arraySameKindCasts,"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same "kind".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same "kind".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n" +arrayShape,"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n" +arrayStream,"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an "objectMode" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +arrayview2iterator,"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n" +arrayview2iteratorRight,"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n" +AsyncIteratorSymbol,"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n" +bartlettTest,"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups })\n\n" +base.abs,"\nbase.abs( x )\n Computes the absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n" +base.abs2,"\nbase.abs2( x )\n Computes the squared absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n" +base.absdiff,"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( {{alias:@stdlib/constants/math/float64-pinf}}, {{alias:@stdlib/constants/math/float64-ninf}} )\n Infinity\n > d = base.absdiff( {{alias:@stdlib/constants/math/float64-pinf}}, {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n\n" +base.absInt32,"\nbase.absInt32( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.absInt32( -1|0 )\n 1\n > v = base.absInt32( 2|0 )\n 2\n > v = base.absInt32( 0|0 )\n 0\n\n" +base.acos,"\nbase.acos( x )\n Compute the arccosine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n" +base.acosh,"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n" +base.acoth,"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent (in radians).\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n" +base.acovercos,"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n" +base.acoversin,"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n" +base.ahavercos,"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n" +base.ahaversin,"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n" +base.asin,"\nbase.asin( x )\n Computes the arcsine of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.0\n > y = base.asin( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n" +base.asinh,"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( {{alias:@stdlib/constants/math/float64-ninf}} )\n -Infinity\n > y = base.asinh( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n\n" +base.atan,"\nbase.atan( x )\n Computes the arctangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -{{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~-1.004\n > y = base.atan( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n" +base.atan2,"\nbase.atan2( y, x )\n Evaluates the arctangent of the quotient of two numbers.\n\n Parameters\n ----------\n y: number\n Numerator.\n\n x: number\n Denominator.\n\n Returns\n -------\n out: number\n Arctangent of `y/x` (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n" +base.atanh,"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n" +base.avercos,"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n" +base.aversin,"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n" +base.bernoulli,"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.0\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n" +base.besselj0,"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.besselj0( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n" +base.besselj1,"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.besselj1( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n" +base.bessely0,"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.bessely0( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n" +base.bessely1,"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.bessely1( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n" +base.beta,"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n" +base.betainc,"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n" +base.betaincinv,"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n" +base.betaln,"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n" +base.binet,"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n" +base.binomcoef,"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n" +base.binomcoefln,"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n" +base.boxcox,"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n" +base.boxcox1p,"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n" +base.boxcox1pinv,"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n" +base.boxcoxinv,"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n" +base.cabs,"\nbase.cabs( re, im )\n Computes the absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( 5.0, 3.0 )\n ~5.831\n\n" +base.cabs2,"\nbase.cabs2( re, im )\n Computes the squared absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( 5.0, 3.0 )\n 34.0\n\n" +base.cadd,"\nbase.cadd( [out,] re1, im1, re2, im2 )\n Adds two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cadd( 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float32}}( 2 );\n > y = base.cadd( out, 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n > var bool = ( y === out )\n true\n\n" +base.cbrt,"\nbase.cbrt( x )\n Computes the cube root.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n" +base.cceil,"\nbase.cceil( [out,] re, im )\n Rounds a complex number toward positive infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceil( 5.5, 3.3 )\n [ 6.0, 4.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cceil( out, 5.5, 3.3 )\n [ 6.0, 4.0 ]\n > var bool = ( v === out )\n true\n\n" +base.cceiln,"\nbase.cceiln( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward positive\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cceiln( out, 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n > var bool = ( v === out )\n true\n\n" +base.ccis,"\nbase.ccis( [out,] re, im )\n Computes the cis function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.ccis( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > var y = base.ccis( 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.ccis( out, 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n" +base.cdiv,"\nbase.cdiv( [out,] re1, im1, re2, im2 )\n Divides two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cdiv( -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cdiv( out, -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n" +base.ceil,"\nbase.ceil( x )\n Rounds a numeric value toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n" +base.ceil2,"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n" +base.ceil10,"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n" +base.ceilb,"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n" +base.ceiln,"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n" +base.ceilsd,"\nbase.ceilsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1 )\n 4.0\n > y = base.ceilsd( 12368.0, 2 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n" +base.cexp,"\nbase.cexp( [out,] re, im )\n Computes the exponential function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cexp( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > y = base.cexp( 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cexp( out, 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n" +base.cflipsign,"\nbase.cflipsign( [out,] re, im, y )\n Returns a complex number with the same magnitude as `z` and the sign of\n `y*z`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.cflipsign( -4.2, 5.5, -9 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cflipsign( out, -4.2, 5.5, 8 )\n [ -4.2, 5.5 ]\n > var bool = ( v === out )\n true\n\n" +base.cfloor,"\nbase.cfloor( [out,] re, im )\n Rounds a complex number toward negative infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cfloor( 5.5, 3.3 )\n [ 5.0, 3.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cfloor( out, 5.5, 3.3 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n" +base.cfloorn,"\nbase.cfloorn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward negative\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cfloorn( 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cfloorn( out, 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n > var bool = ( v === out )\n true\n\n" +base.cinv,"\nbase.cinv( [out,] re, im )\n Computes the inverse of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cinv( 2.0, 4.0 )\n [ 0.1, -0.2 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cinv( out, 2.0, 4.0 )\n [ 0.1, -0.2 ]\n > var bool = ( v === out )\n true\n\n" +base.clamp,"\nbase.clamp( v, min, max )\n Restricts a value to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n" +base.cmul,"\nbase.cmul( [out,] re1, im1, re2, im2 )\n Multiplies two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.cmul( 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cmul( out, 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n > var bool = ( v === out )\n true\n\n" +base.cneg,"\nbase.cneg( [out,] re, im )\n Negates a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Negated components.\n\n Examples\n --------\n > var out = base.cneg( -4.2, 5.5 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cneg( out, -4.2, 5.5 )\n [ 4.2, -5.5 ]\n > var bool = ( v === out )\n true\n\n" +base.continuedFraction,"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 + a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n" +base.copysign,"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n" +base.cos,"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~0.707\n > y = base.cos( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n" +base.cosh,"\nbase.cosh( x )\n Computes the hyperbolic cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n" +base.cosm1,"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~-0.293\n > y = base.cosm1( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n" +base.cospi,"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n" +base.covercos,"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n" +base.coversin,"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n" +base.cphase,"\nbase.cphase( re, im )\n Computes the argument of a complex number in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( 5.0, 3.0 )\n ~0.5404\n\n" +base.cpolar,"\nbase.cpolar( [out,] re, im )\n Returns the absolute value and phase of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cpolar( out, 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n" +base.cround,"\nbase.cround( [out,] re, im )\n Rounds a complex number to the nearest integer.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cround( 5.5, 3.3 )\n [ 6.0, 3.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cround( out, 5.5, 3.3 )\n [ 6.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n" +base.croundn,"\nbase.croundn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.croundn( 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.croundn( out, 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n > var bool = ( v === out )\n true\n\n" +base.csignum,"\nbase.csignum( [out,] re, im )\n Evaluates the signum function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.csignum( -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.csignum( out, -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n > var bool = ( v === out )\n true\n\n" +base.csub,"\nbase.csub( [out,] re1, im1, re2, im2 )\n Subtracts two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.csub( 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.csub( out, 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n > var bool = ( v === out )\n true\n\n" +base.dasum,"\nbase.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.dasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.dasum( N, x1, stride )\n 12.0\n\n\nbase.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n\nbase.dasum.wasm( [options] )\n Returns a memory managed function to compute the sum of absolute values.\n\n For an externally defined `Float64Array`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.dasum.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var bytes = wasm.malloc( N * 8 );\n\n // Create a Float64Array view:\n > var view = new {{alias:@stdlib/array/float64}}( bytes.buffer, bytes.byteOffset, N );\n\n // Copy data to the heap:\n > view.set( [ 1.0, -2.0, 3.0, -4.0, 5.0 ] );\n\n // Compute the sum of absolute values (passing in the heap buffer):\n > var s = wasm( N, bytes, 1 )\n 15.0\n\n // Free the memory:\n > wasm.free( bytes );\n\n" +base.daxpy,"\nbase.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.daxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.daxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.daxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.wasm( [options] )\n Returns a memory managed function to multiply `x` by a constant `alpha` and\n add the result to `y`.\n\n For externally defined `Float64Arrays`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.daxpy.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var xbytes = wasm.malloc( N * 8 );\n > var ybytes = wasm.malloc( N * 8 );\n\n // Create Float64Array views:\n > var x = new {{alias:@stdlib/array/float64}}( xbytes.buffer, xbytes.byteOffset, N );\n > var y = new {{alias:@stdlib/array/float64}}( ybytes.buffer, ybytes.byteOffset, N );\n\n // Copy data to the heap:\n > x.set( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > y.set( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n\n // Multiply and add alpha:\n > var alpha = 5.0;\n > wasm( x.length, alpha, xbytes, 1, ybytes, 1 );\n > y\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Free the memory:\n > wasm.free( xbytes );\n > wasm.free( ybytes );\n\n" +base.dcopy,"\nbase.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.dcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.dcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.dcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n" +base.deg2rad,"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n" +base.digamma,"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n" +base.diracDelta,"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n" +base.dists.arcsine.Arcsine,"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n" +base.dists.arcsine.cdf,"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n" +base.dists.arcsine.entropy,"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n" +base.dists.arcsine.kurtosis,"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n" +base.dists.arcsine.logcdf,"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n" +base.dists.arcsine.logpdf,"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n" +base.dists.arcsine.mean,"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n" +base.dists.arcsine.median,"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n" +base.dists.arcsine.mode,"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n" +base.dists.arcsine.pdf,"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n" +base.dists.arcsine.quantile,"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n" +base.dists.arcsine.skewness,"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n" +base.dists.arcsine.stdev,"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n" +base.dists.arcsine.variance,"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n" +base.dists.bernoulli.Bernoulli,"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n" +base.dists.bernoulli.cdf,"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n" +base.dists.bernoulli.entropy,"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n" +base.dists.bernoulli.kurtosis,"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n" +base.dists.bernoulli.mean,"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n" +base.dists.bernoulli.median,"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n" +base.dists.bernoulli.mgf,"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n" +base.dists.bernoulli.mode,"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n" +base.dists.bernoulli.pmf,"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n" +base.dists.bernoulli.quantile,"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n" +base.dists.bernoulli.skewness,"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n" +base.dists.bernoulli.stdev,"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n" +base.dists.bernoulli.variance,"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n" +base.dists.beta.Beta,"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n" +base.dists.beta.cdf,"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n" +base.dists.beta.entropy,"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n" +base.dists.beta.kurtosis,"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n" +base.dists.beta.logcdf,"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n" +base.dists.beta.logpdf,"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n" +base.dists.beta.mean,"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n" +base.dists.beta.median,"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n" +base.dists.beta.mgf,"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n" +base.dists.beta.mode,"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n" +base.dists.beta.pdf,"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n" +base.dists.beta.quantile,"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n" +base.dists.beta.skewness,"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n" +base.dists.beta.stdev,"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n" +base.dists.beta.variance,"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n" +base.dists.betaprime.BetaPrime,"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n" +base.dists.betaprime.cdf,"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n" +base.dists.betaprime.kurtosis,"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n" +base.dists.betaprime.logcdf,"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n" +base.dists.betaprime.logpdf,"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n" +base.dists.betaprime.mean,"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n" +base.dists.betaprime.mode,"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n" +base.dists.betaprime.pdf,"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n" +base.dists.betaprime.quantile,"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n" +base.dists.betaprime.skewness,"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n" +base.dists.betaprime.stdev,"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n" +base.dists.betaprime.variance,"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n" +base.dists.binomial.Binomial,"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n" +base.dists.binomial.cdf,"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n" +base.dists.binomial.entropy,"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n" +base.dists.binomial.kurtosis,"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n" +base.dists.binomial.logpmf,"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n" +base.dists.binomial.mean,"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n" +base.dists.binomial.median,"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n" +base.dists.binomial.mgf,"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n" +base.dists.binomial.mode,"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n" +base.dists.binomial.pmf,"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n" +base.dists.binomial.quantile,"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n" +base.dists.binomial.skewness,"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n" +base.dists.binomial.stdev,"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n" +base.dists.binomial.variance,"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n" +base.dists.cauchy.Cauchy,"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n" +base.dists.cauchy.cdf,"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n" +base.dists.cauchy.entropy,"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n" +base.dists.cauchy.logcdf,"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n" +base.dists.cauchy.logpdf,"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n" +base.dists.cauchy.median,"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n" +base.dists.cauchy.mode,"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n" +base.dists.cauchy.pdf,"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n" +base.dists.cauchy.quantile,"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n" +base.dists.chi.cdf,"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n" +base.dists.chi.Chi,"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n" +base.dists.chi.entropy,"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n" +base.dists.chi.kurtosis,"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n" +base.dists.chi.logpdf,"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n" +base.dists.chi.mean,"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n" +base.dists.chi.mode,"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n" +base.dists.chi.pdf,"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n" +base.dists.chi.quantile,"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n" +base.dists.chi.skewness,"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n" +base.dists.chi.stdev,"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n" +base.dists.chi.variance,"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n" +base.dists.chisquare.cdf,"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n" +base.dists.chisquare.ChiSquare,"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n" +base.dists.chisquare.entropy,"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n" +base.dists.chisquare.kurtosis,"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n" +base.dists.chisquare.logpdf,"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n" +base.dists.chisquare.mean,"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n" +base.dists.chisquare.mode,"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n" +base.dists.chisquare.pdf,"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n" +base.dists.chisquare.quantile,"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n" +base.dists.chisquare.skewness,"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n" +base.dists.chisquare.stdev,"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n" +base.dists.chisquare.variance,"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n" +base.dists.cosine.cdf,"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n" +base.dists.cosine.Cosine,"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n" +base.dists.cosine.kurtosis,"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n" +base.dists.cosine.logcdf,"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n" +base.dists.cosine.logpdf,"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n" +base.dists.cosine.mean,"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n" +base.dists.cosine.median,"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n" +base.dists.cosine.mgf,"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n" +base.dists.cosine.mode,"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n" +base.dists.cosine.pdf,"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n" +base.dists.cosine.quantile,"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n" +base.dists.cosine.skewness,"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n" +base.dists.cosine.stdev,"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n" +base.dists.cosine.variance,"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n" +base.dists.degenerate.cdf,"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n" +base.dists.degenerate.Degenerate,"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n" +base.dists.degenerate.entropy,"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n" +base.dists.degenerate.logcdf,"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n" +base.dists.degenerate.logpdf,"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n" +base.dists.degenerate.logpmf,"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n" +base.dists.degenerate.mean,"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n" +base.dists.degenerate.median,"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n" +base.dists.degenerate.mgf,"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n" +base.dists.degenerate.mode,"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n" +base.dists.degenerate.pdf,"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n" +base.dists.degenerate.pmf,"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n" +base.dists.degenerate.quantile,"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n" +base.dists.degenerate.stdev,"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n" +base.dists.degenerate.variance,"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n" +base.dists.discreteUniform.cdf,"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n" +base.dists.discreteUniform.DiscreteUniform,"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n" +base.dists.discreteUniform.kurtosis,"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n" +base.dists.discreteUniform.logcdf,"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n" +base.dists.discreteUniform.logpmf,"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n" +base.dists.discreteUniform.mean,"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n" +base.dists.discreteUniform.median,"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n" +base.dists.discreteUniform.mgf,"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n" +base.dists.discreteUniform.pmf,"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n" +base.dists.discreteUniform.quantile,"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n" +base.dists.discreteUniform.skewness,"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n" +base.dists.discreteUniform.stdev,"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n" +base.dists.discreteUniform.variance,"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n" +base.dists.erlang.cdf,"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n" +base.dists.erlang.entropy,"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n" +base.dists.erlang.Erlang,"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n" +base.dists.erlang.kurtosis,"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n" +base.dists.erlang.logpdf,"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n" +base.dists.erlang.mean,"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n" +base.dists.erlang.mgf,"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n" +base.dists.erlang.mode,"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n" +base.dists.erlang.pdf,"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n" +base.dists.erlang.quantile,"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n" +base.dists.erlang.skewness,"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n" +base.dists.erlang.stdev,"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n" +base.dists.erlang.variance,"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n" +base.dists.exponential.cdf,"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n" +base.dists.exponential.entropy,"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n" +base.dists.exponential.Exponential,"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n" +base.dists.exponential.kurtosis,"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n" +base.dists.exponential.logcdf,"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n" +base.dists.exponential.logpdf,"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n" +base.dists.exponential.mean,"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n" +base.dists.exponential.median,"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n" +base.dists.exponential.mode,"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n" +base.dists.exponential.pdf,"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n" +base.dists.exponential.quantile,"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n" +base.dists.exponential.skewness,"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n" +base.dists.exponential.stdev,"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n" +base.dists.exponential.variance,"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n" +base.dists.f.cdf,"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n" +base.dists.f.entropy,"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of a F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n" +base.dists.f.F,"\nbase.dists.f.F( [d1, d2] )\n Returns a F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n" +base.dists.f.kurtosis,"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of a F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n" +base.dists.f.mean,"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of a F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n" +base.dists.f.mode,"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of a F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n" +base.dists.f.pdf,"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for a F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n" +base.dists.f.quantile,"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for a F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n" +base.dists.f.skewness,"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of a F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n" +base.dists.f.stdev,"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of a F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n" +base.dists.f.variance,"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of a F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n" +base.dists.frechet.cdf,"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n" +base.dists.frechet.entropy,"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n" +base.dists.frechet.Frechet,"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n" +base.dists.frechet.kurtosis,"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n" +base.dists.frechet.logcdf,"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n" +base.dists.frechet.logpdf,"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n" +base.dists.frechet.mean,"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n" +base.dists.frechet.median,"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n" +base.dists.frechet.mode,"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n" +base.dists.frechet.pdf,"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n" +base.dists.frechet.quantile,"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n" +base.dists.frechet.skewness,"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n" +base.dists.frechet.stdev,"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n" +base.dists.frechet.variance,"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n" +base.dists.gamma.cdf,"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n" +base.dists.gamma.entropy,"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n" +base.dists.gamma.Gamma,"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n" +base.dists.gamma.kurtosis,"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n" +base.dists.gamma.logpdf,"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n" +base.dists.gamma.mean,"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n" +base.dists.gamma.mgf,"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n" +base.dists.gamma.mode,"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n" +base.dists.gamma.pdf,"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n" +base.dists.gamma.quantile,"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n" +base.dists.gamma.skewness,"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n" +base.dists.gamma.stdev,"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n" +base.dists.gamma.variance,"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n" +base.dists.geometric.cdf,"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n" +base.dists.geometric.entropy,"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n" +base.dists.geometric.Geometric,"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n" +base.dists.geometric.kurtosis,"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n" +base.dists.geometric.logcdf,"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n" +base.dists.geometric.logpmf,"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n" +base.dists.geometric.mean,"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n" +base.dists.geometric.median,"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n" +base.dists.geometric.mgf,"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n" +base.dists.geometric.mode,"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n" +base.dists.geometric.pmf,"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n" +base.dists.geometric.quantile,"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n" +base.dists.geometric.skewness,"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n" +base.dists.geometric.stdev,"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n" +base.dists.geometric.variance,"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n" +base.dists.gumbel.cdf,"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n" +base.dists.gumbel.entropy,"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n" +base.dists.gumbel.Gumbel,"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n" +base.dists.gumbel.kurtosis,"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n" +base.dists.gumbel.logcdf,"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n" +base.dists.gumbel.logpdf,"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n" +base.dists.gumbel.mean,"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n" +base.dists.gumbel.median,"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n" +base.dists.gumbel.mgf,"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n" +base.dists.gumbel.mode,"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n" +base.dists.gumbel.pdf,"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n" +base.dists.gumbel.quantile,"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n" +base.dists.gumbel.skewness,"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n" +base.dists.gumbel.stdev,"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n" +base.dists.gumbel.variance,"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n" +base.dists.hypergeometric.cdf,"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n" +base.dists.hypergeometric.Hypergeometric,"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n" +base.dists.hypergeometric.kurtosis,"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n" +base.dists.hypergeometric.logpmf,"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n" +base.dists.hypergeometric.mean,"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n" +base.dists.hypergeometric.mode,"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n" +base.dists.hypergeometric.pmf,"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n" +base.dists.hypergeometric.quantile,"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n" +base.dists.hypergeometric.skewness,"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n" +base.dists.hypergeometric.stdev,"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n" +base.dists.hypergeometric.variance,"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n" +base.dists.invgamma.cdf,"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n" +base.dists.invgamma.entropy,"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n" +base.dists.invgamma.InvGamma,"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n" +base.dists.invgamma.kurtosis,"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n" +base.dists.invgamma.logpdf,"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n" +base.dists.invgamma.mean,"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n" +base.dists.invgamma.mode,"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n" +base.dists.invgamma.pdf,"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n" +base.dists.invgamma.quantile,"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n" +base.dists.invgamma.skewness,"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n" +base.dists.invgamma.stdev,"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n" +base.dists.invgamma.variance,"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n" +base.dists.kumaraswamy.cdf,"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n" +base.dists.kumaraswamy.Kumaraswamy,"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n" +base.dists.kumaraswamy.kurtosis,"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n" +base.dists.kumaraswamy.logcdf,"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n" +base.dists.kumaraswamy.logpdf,"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n" +base.dists.kumaraswamy.mean,"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n" +base.dists.kumaraswamy.median,"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n" +base.dists.kumaraswamy.mode,"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n" +base.dists.kumaraswamy.pdf,"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n" +base.dists.kumaraswamy.quantile,"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n" +base.dists.kumaraswamy.skewness,"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n" +base.dists.kumaraswamy.stdev,"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n" +base.dists.kumaraswamy.variance,"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n" +base.dists.laplace.cdf,"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n" +base.dists.laplace.entropy,"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n" +base.dists.laplace.kurtosis,"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n" +base.dists.laplace.Laplace,"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n" +base.dists.laplace.logcdf,"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n" +base.dists.laplace.logpdf,"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n" +base.dists.laplace.mean,"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n" +base.dists.laplace.median,"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n" +base.dists.laplace.mgf,"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n" +base.dists.laplace.mode,"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n" +base.dists.laplace.pdf,"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n" +base.dists.laplace.quantile,"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n" +base.dists.laplace.skewness,"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n" +base.dists.laplace.stdev,"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n" +base.dists.laplace.variance,"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n" +base.dists.levy.cdf,"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n" +base.dists.levy.entropy,"\nbase.dists.levy.entropy( μ, c )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n" +base.dists.levy.Levy,"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n" +base.dists.levy.logcdf,"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n" +base.dists.levy.logpdf,"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n" +base.dists.levy.mean,"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n" +base.dists.levy.median,"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n" +base.dists.levy.mode,"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n" +base.dists.levy.pdf,"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n" +base.dists.levy.quantile,"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n" +base.dists.levy.stdev,"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n" +base.dists.levy.variance,"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n" +base.dists.logistic.cdf,"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n" +base.dists.logistic.entropy,"\nbase.dists.logistic.entropy( μ, s )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n" +base.dists.logistic.kurtosis,"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n" +base.dists.logistic.logcdf,"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n" +base.dists.logistic.Logistic,"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n" +base.dists.logistic.logpdf,"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n" +base.dists.logistic.mean,"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n" +base.dists.logistic.median,"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n" +base.dists.logistic.mgf,"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n" +base.dists.logistic.mode,"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n" +base.dists.logistic.pdf,"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n" +base.dists.logistic.quantile,"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n" +base.dists.logistic.skewness,"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n" +base.dists.logistic.stdev,"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n" +base.dists.logistic.variance,"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n" +base.dists.lognormal.cdf,"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n" +base.dists.lognormal.entropy,"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n" +base.dists.lognormal.kurtosis,"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n" +base.dists.lognormal.LogNormal,"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n" +base.dists.lognormal.logpdf,"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n" +base.dists.lognormal.mean,"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n" +base.dists.lognormal.median,"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n" +base.dists.lognormal.mode,"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n" +base.dists.lognormal.pdf,"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n" +base.dists.lognormal.quantile,"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n" +base.dists.lognormal.skewness,"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n" +base.dists.lognormal.stdev,"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n" +base.dists.lognormal.variance,"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n" +base.dists.negativeBinomial.cdf,"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n" +base.dists.negativeBinomial.kurtosis,"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n" +base.dists.negativeBinomial.logpmf,"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n" +base.dists.negativeBinomial.mean,"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n" +base.dists.negativeBinomial.mgf,"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n" +base.dists.negativeBinomial.mode,"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n" +base.dists.negativeBinomial.NegativeBinomial,"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n" +base.dists.negativeBinomial.pmf,"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n" +base.dists.negativeBinomial.quantile,"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n" +base.dists.negativeBinomial.skewness,"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n" +base.dists.negativeBinomial.stdev,"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n" +base.dists.negativeBinomial.variance,"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n" +base.dists.normal.cdf,"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n" +base.dists.normal.entropy,"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n" +base.dists.normal.kurtosis,"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n" +base.dists.normal.logpdf,"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n" +base.dists.normal.mean,"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n" +base.dists.normal.median,"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n" +base.dists.normal.mgf,"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n" +base.dists.normal.mode,"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n" +base.dists.normal.Normal,"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n" +base.dists.normal.pdf,"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n" +base.dists.normal.quantile,"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n" +base.dists.normal.skewness,"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n" +base.dists.normal.stdev,"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n" +base.dists.normal.variance,"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n" +base.dists.pareto1.cdf,"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n" +base.dists.pareto1.entropy,"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n" +base.dists.pareto1.kurtosis,"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n" +base.dists.pareto1.logcdf,"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n" +base.dists.pareto1.logpdf,"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n" +base.dists.pareto1.mean,"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n" +base.dists.pareto1.median,"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n" +base.dists.pareto1.mode,"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n" +base.dists.pareto1.Pareto1,"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n" +base.dists.pareto1.pdf,"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n" +base.dists.pareto1.quantile,"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n" +base.dists.pareto1.skewness,"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n" +base.dists.pareto1.variance,"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n" +base.dists.poisson.cdf,"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n" +base.dists.poisson.entropy,"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n" +base.dists.poisson.kurtosis,"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n" +base.dists.poisson.logpmf,"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n" +base.dists.poisson.mean,"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n" +base.dists.poisson.median,"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n" +base.dists.poisson.mode,"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n" +base.dists.poisson.pmf,"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n" +base.dists.poisson.Poisson,"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n" +base.dists.poisson.quantile,"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n" +base.dists.poisson.skewness,"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n" +base.dists.poisson.stdev,"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n" +base.dists.poisson.variance,"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n" +base.dists.rayleigh.cdf,"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n" +base.dists.rayleigh.entropy,"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n" +base.dists.rayleigh.kurtosis,"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n" +base.dists.rayleigh.logcdf,"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n" +base.dists.rayleigh.logpdf,"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n" +base.dists.rayleigh.mean,"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n" +base.dists.rayleigh.median,"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n" +base.dists.rayleigh.mgf,"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n" +base.dists.rayleigh.mode,"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n" +base.dists.rayleigh.pdf,"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n" +base.dists.rayleigh.quantile,"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n" +base.dists.rayleigh.Rayleigh,"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n" +base.dists.rayleigh.skewness,"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n" +base.dists.rayleigh.stdev,"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n" +base.dists.rayleigh.variance,"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n" +base.dists.t.cdf,"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n" +base.dists.t.entropy,"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n" +base.dists.t.kurtosis,"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n" +base.dists.t.mean,"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n" +base.dists.t.median,"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n" +base.dists.t.mode,"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n" +base.dists.t.pdf,"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n" +base.dists.t.quantile,"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n" +base.dists.t.skewness,"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n" +base.dists.t.stdev,"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n" +base.dists.t.T,"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n" +base.dists.t.variance,"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n" +base.dists.triangular.cdf,"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n" +base.dists.triangular.entropy,"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n" +base.dists.triangular.kurtosis,"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n" +base.dists.triangular.logcdf,"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n" +base.dists.triangular.logpdf,"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n" +base.dists.triangular.mean,"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n" +base.dists.triangular.median,"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n" +base.dists.triangular.mgf,"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n" +base.dists.triangular.mode,"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n" +base.dists.triangular.pdf,"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n" +base.dists.triangular.quantile,"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n" +base.dists.triangular.skewness,"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n" +base.dists.triangular.stdev,"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n" +base.dists.triangular.Triangular,"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n" +base.dists.triangular.variance,"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n" +base.dists.uniform.cdf,"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n" +base.dists.uniform.entropy,"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n" +base.dists.uniform.kurtosis,"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n" +base.dists.uniform.logcdf,"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n" +base.dists.uniform.logpdf,"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n" +base.dists.uniform.mean,"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n" +base.dists.uniform.median,"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n" +base.dists.uniform.mgf,"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n" +base.dists.uniform.pdf,"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n" +base.dists.uniform.quantile,"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n" +base.dists.uniform.skewness,"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n" +base.dists.uniform.stdev,"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n" +base.dists.uniform.Uniform,"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n" +base.dists.uniform.variance,"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n" +base.dists.weibull.cdf,"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n" +base.dists.weibull.entropy,"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n" +base.dists.weibull.kurtosis,"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n" +base.dists.weibull.logcdf,"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n" +base.dists.weibull.logpdf,"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n" +base.dists.weibull.mean,"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n" +base.dists.weibull.median,"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n" +base.dists.weibull.mgf,"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n" +base.dists.weibull.mode,"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n" +base.dists.weibull.pdf,"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n" +base.dists.weibull.quantile,"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n" +base.dists.weibull.skewness,"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n" +base.dists.weibull.stdev,"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n" +base.dists.weibull.variance,"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n" +base.dists.weibull.Weibull,"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n" +base.ellipe,"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n > y = base.ellipe( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n" +base.ellipk,"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n > y = base.ellipk( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n" +base.epsdiff,"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n" +base.erf,"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n" +base.erfc,"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.erfc( {{alias:@stdlib/constants/math/float64-ninf}} )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n" +base.erfcinv,"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n" +base.erfinv,"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n" +base.eta,"\nbase.eta( s )\n Evaluates the Dirichlet eta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n" +base.evalpoly,"\nbase.evalpoly( c, x )\n Evaluates a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n" +base.evalrational,"\nbase.evalrational( P, Q, x )\n Evaluates a rational function.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n" +base.exp,"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n" +base.exp2,"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n" +base.exp10,"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n" +base.expit,"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n" +base.expm1,"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n" +base.expm1rel,"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n \n" +base.exponent,"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n" +base.exponentf,"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e34 ) )\n 114\n > exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n" +base.factorial,"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n" +base.factorialln,"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n" +base.fallingFactorial,"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n" +base.fibonacci,"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n" +base.fibonacciIndex,"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n" +base.fibpoly,"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n" +base.flipsign,"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`, else behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.14, 10.0 )\n -3.14\n > z = base.flipsign( -3.14, -1.0 )\n 3.14\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.14, -0.0 )\n 3.14\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n" +base.float32ToInt32,"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( 4294967295.0 ) )\n -1\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14 ) )\n 3\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n -3\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( NaN ) )\n 0\n > y = base.float32ToInt32( {{alias:@stdlib/constants/math/float32-pinf}} )\n 0\n > y = base.float32ToInt32( {{alias:@stdlib/constants/math/float32-ninf}} )\n 0\n" +base.float32ToUint32,"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( 4294967297.0 ) )\n 1\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14 ) )\n 3\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( NaN ) )\n 0\n > y = base.float32ToUint32( {{alias:@stdlib/constants/math/float32-pinf}} )\n 0\n > y = base.float32ToUint32( {{alias:@stdlib/constants/math/float32-ninf}} )\n 0\n" +base.float64ToFloat32,"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n" +base.float64ToInt32,"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0\n > y = base.float64ToInt32( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0\n" +base.float64ToUint32,"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0\n > y = base.float64ToUint32( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0\n" +base.floor,"\nbase.floor( x )\n Rounds a numeric value toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n" +base.floor2,"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n" +base.floor10,"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n" +base.floorb,"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n" +base.floorn,"\nbase.floorn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward negative\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n" +base.floorsd,"\nbase.floorsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5 )\n 3.1415\n > y = base.floorsd( 3.14159, 1 )\n 3.0\n > y = base.floorsd( 12368.0, 2 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n" +base.fresnel,"\nbase.fresnel( [out,] x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.fresnel( out, 0.0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n" +base.fresnelc,"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( {{alias:@stdlib/constants/math/float64-pinf}} )\n ~0.5\n > y = base.fresnelc( {{alias:@stdlib/constants/math/float64-ninf}} )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n" +base.fresnels,"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( {{alias:@stdlib/constants/math/float64-pinf}} )\n ~0.5\n > y = base.fresnels( {{alias:@stdlib/constants/math/float64-ninf}} )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n" +base.frexp,"\nbase.frexp( [out,] x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, 0 ]\n > out = base.frexp( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var y = base.frexp( out, 4.0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n" +base.fromBinaryString,"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n" +base.fromBinaryStringf,"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n" +base.fromBinaryStringUint8,"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n" +base.fromBinaryStringUint16,"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n" +base.fromBinaryStringUint32,"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n" +base.fromWordf,"\nbase.fromWordf( x )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n" +base.fromWords,"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n" +base.gamma,"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n" +base.gamma1pm1,"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n" +base.gammaDeltaRatio,"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n" +base.gammainc,"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n" +base.gammaincinv,"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n" +base.gammaLanczosSum,"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n" +base.gammaLanczosSumExpGScaled,"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n" +base.gammaln,"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n" +base.gasum,"\nbase.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.gasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.gasum( N, x1, stride )\n 12.0\n\n\nbase.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > sum = base.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n" +base.gaxpy,"\nbase.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gaxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.gaxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gaxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n" +base.gcd,"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n" +base.gcopy,"\nbase.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.gcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n" +base.getHighWord,"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n" +base.getLowWord,"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n" +base.hacovercos,"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n" +base.hacoversin,"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n" +base.havercos,"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n" +base.haversin,"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n" +base.heaviside,"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n" +base.hermitepoly,"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n" +base.hypot,"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n" +base.imul,"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n" +base.imuldw,"\nbase.imuldw( [out,] a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n" +base.int32ToUint32,"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( {{alias:@stdlib/number/float64/base/to-int32}}( -32 ) )\n 4294967264\n > y = base.int32ToUint32( {{alias:@stdlib/number/float64/base/to-int32}}( 3 ) )\n 3\n\n" +base.inv,"\nbase.inv( x )\n Computes the multiplicative inverse of `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n" +base.isEven,"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n" +base.isEvenInt32,"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n" +base.isFinite,"\nbase.isFinite( x )\n Tests if a numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( {{alias:@stdlib/constants/math/float64-pinf}} )\n false\n > bool = base.isFinite( {{alias:@stdlib/constants/math/float64-ninf}} )\n false\n\n" +base.isInfinite,"\nbase.isInfinite( x )\n Tests if a numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( {{alias:@stdlib/constants/math/float64-pinf}} )\n true\n > bool = base.isInfinite( {{alias:@stdlib/constants/math/float64-ninf}} )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n" +base.isInteger,"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n" +base.isnan,"\nbase.isnan( x )\n Tests if a numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n" +base.isNegativeInteger,"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n" +base.isNegativeZero,"\nbase.isNegativeZero( x )\n Tests if a numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n" +base.isNonNegativeInteger,"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n" +base.isNonPositiveInteger,"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n" +base.isOdd,"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n" +base.isOddInt32,"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n" +base.isPositiveInteger,"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n" +base.isPositiveZero,"\nbase.isPositiveZero( x )\n Tests if a numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n" +base.isPow2Uint32,"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n" +base.isProbability,"\nbase.isProbability( x )\n Tests if a numeric value is a probability.\n\n A probability is defined as a numeric value on the closed interval `[0,1]`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n" +base.isSafeInteger,"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is "safe" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n" +base.kernelBetainc,"\nbase.kernelBetainc( [out,] x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.32, 1.6 ]\n\n > out = new Array( 2 );\n > var v = base.kernelBetainc( out, 0.2, 1.0, 2.0, true, true )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n" +base.kernelBetaincinv,"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n" +base.kernelCos,"\nbase.kernelCos( x, y )\n Computes the cosine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n" +base.kernelSin,"\nbase.kernelSin( x, y )\n Computes the sine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n" +base.kernelTan,"\nbase.kernelTan( x, y, k )\n Computes the tangent of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n" +base.kroneckerDelta,"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n" +base.lcm,"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n" +base.ldexp,"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( {{alias:@stdlib/constants/math/float64-pinf}}, 11 )\n Infinity\n > x = base.ldexp( {{alias:@stdlib/constants/math/float64-ninf}}, -118 )\n -Infinity\n\n" +base.ln,"\nbase.ln( x )\n Evaluates the natural logarithm.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n" +base.log,"\nbase.log( x, b )\n Computes the base `b` logarithm of `x`.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n" +base.log1mexp,"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n" +base.log1p,"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n" +base.log1pexp,"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n" +base.log2,"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n" +base.log10,"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n" +base.logaddexp,"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n" +base.logit,"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n" +base.lucas,"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n" +base.lucaspoly,"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n" +base.max,"\nbase.max( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n" +base.maxabs,"\nbase.maxabs( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n" +base.min,"\nbase.min( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n" +base.minabs,"\nbase.minabs( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n" +base.minmax,"\nbase.minmax( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmax( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmax( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n" +base.minmaxabs,"\nbase.minmaxabs( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabs( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmaxabs( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n" +base.modf,"\nbase.modf( [out,] x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n parts: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, +0.0 ]\n > parts = base.modf( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > parts = base.modf( out, 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n\n" +base.ndarray,"\nbase.ndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarray( 'float64', 3 )\n \n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n" +base.ndarrayMemoized,"\nbase.ndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarrayMemoized( 'float64', 3 )\n \n > var f = base.ndarrayMemoized( 'float64', 3 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n" +base.negafibonacci,"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n" +base.negalucas,"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n" +base.nonfibonacci,"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n" +base.normalize,"\nbase.normalize( [out,] x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*{{alias:@stdlib/math/base/special/pow}}(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, 0 ]\n > out = base.normalize( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.normalize( out, 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > bool = ( v === out )\n true\n\n" +base.normalizef,"\nbase.normalizef( [out,] x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( {{alias:@stdlib/number/float64/base/to-float32}}( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*{{alias:@stdlib/math/base/special/pow}}(2,exp) === {{alias:@stdlib/number/float64/base/to-float32}}(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( {{alias:@stdlib/constants/math/float32-pinf}} )\n [ Infinity, 0 ]\n > out = base.normalizef( {{alias:@stdlib/constants/math/float32-ninf}} )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float32}}( 2 );\n > var v = base.normalizef( out, {{alias:@stdlib/number/float64/base/to-float32}}( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n" +base.normhermitepoly,"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n" +base.pdiff,"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n" +base.polygamma,"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n" +base.pow,"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( {{alias:@stdlib/constants/math/float64-pi}}, 5.0 )\n ~306.0197\n > y = base.pow( {{alias:@stdlib/constants/math/float64-pi}}, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n" +base.powm1,"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( {{alias:@stdlib/constants/math/float64-pi}}, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n" +base.rad2deg,"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n 90.0\n > d = base.rad2deg( -{{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( {{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n 29.999999999999996\n\n" +base.ramp,"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n" +base.random.arcsine,"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.bernoulli,"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.beta,"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.betaprime,"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.binomial,"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.boxMuller,"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.cauchy,"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.chi,"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.chisquare,"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.cosine,"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.discreteUniform,"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.erlang,"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.exponential,"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.f,"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.frechet,"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.gamma,"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.geometric,"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.gumbel,"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.hypergeometric,"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.improvedZiggurat,"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.invgamma,"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.kumaraswamy,"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.laplace,"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.levy,"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.logistic,"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.lognormal,"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.minstd,"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the "randomness quality" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.minstdShuffle,"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the "randomness\n quality" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.mt19937,"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[1, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 1\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.negativeBinomial,"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.normal,"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.pareto1,"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.poisson,"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.randi,"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.randn,"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.randu,"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.rayleigh,"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.t,"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function\n returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.triangular,"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.uniform,"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.weibull,"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.reldiff,"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = {{alias:@stdlib/math/base/special/abs}}( x );\n ... y = {{alias:@stdlib/math/base/special/abs}}( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * {{alias:@stdlib/constants/math/float64-eps}};\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n" +base.rempio2,"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = new Array( 2 );\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n" +base.risingFactorial,"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n" +base.rotl32,"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( y )\n '00000000000000000000011000000000'\n\n" +base.rotr32,"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( y )\n '00000000010000000000000000000000'\n\n" +base.round,"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n" +base.round2,"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n" +base.round10,"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n" +base.roundb,"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n" +base.roundn,"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n" +base.roundsd,"\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n" +base.rsqrt,"\nbase.rsqrt( x )\n Computes the reciprocal square root.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n" +base.sasum,"\nbase.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.sasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.sasum( N, x1, stride )\n 12.0\n\n\nbase.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n" +base.saxpy,"\nbase.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.saxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.saxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.saxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n" +base.scopy,"\nbase.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.scopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.scopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.scopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n" +base.setHighWord,"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( {{alias:@stdlib/constants/math/float64-pinf}}, high )\n 1.0\n\n" +base.setLowWord,"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( {{alias:@stdlib/constants/math/float64-pinf}}, low )\n NaN\n > y = base.setLowWord( {{alias:@stdlib/constants/math/float64-ninf}}, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n" +base.sici,"\nbase.sici( [out,] x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > y = base.sici( out, 3.0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n\n" +base.signbit,"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n" +base.signbitf,"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( {{alias:@stdlib/number/float64/base/to-float32}}( 4.0 ) )\n false\n > bool = base.signbitf( {{alias:@stdlib/number/float64/base/to-float32}}( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n" +base.significandf,"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e34 ) )\n 4293751\n > s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e-34 ) )\n 5288021\n > s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n" +base.signum,"\nbase.signum( x )\n Evaluates the signum function.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n" +base.sin,"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.0\n > y = base.sin( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n" +base.sinc,"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n" +base.sincos,"\nbase.sincos( [out,] x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.sincos( out, 0.0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n" +base.sincospi,"\nbase.sincospi( [out,] x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.sincospi( out, 0.0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n" +base.sinh,"\nbase.sinh( x )\n Computes the hyperbolic sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n" +base.sinpi,"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n" +base.spence,"\nbase.spence( x )\n Evaluates Spence’s function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n" +base.sqrt,"\nbase.sqrt( x )\n Computes the principal square root.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n" +base.sqrt1pm1,"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n" +base.sumSeries,"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n" +base.tan,"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -{{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~-1.0\n > y = base.tan( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n" +base.tanh,"\nbase.tanh( x )\n Computes the hyperbolic tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n" +base.toBinaryString,"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-pi}} )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-pinf}} )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-ninf}} )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n" +base.toBinaryStringf,"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( {{alias:@stdlib/constants/math/float64-pi}} ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/constants/math/float32-pinf}} )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/constants/math/float32-ninf}} )\n '11111111100000000000000000000000'\n\n" +base.toBinaryStringUint8,"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint8}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n" +base.toBinaryStringUint16,"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint16}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n" +base.toBinaryStringUint32,"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint32}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n" +base.toWordf,"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = {{alias:@stdlib/number/float64/base/to-float32}}( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n" +base.toWords,"\nbase.toWords( [out,] x )\n Splits a floating-point number into a higher order word (unsigned 32-bit\n integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/uint32}}( 2 );\n > w = base.toWords( out, 3.14e201 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n" +base.trigamma,"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n" +base.trunc,"\nbase.trunc( x )\n Rounds a numeric value toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n" +base.trunc2,"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n" +base.trunc10,"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n" +base.truncb,"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n" +base.truncn,"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n" +base.truncsd,"\nbase.truncsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5 )\n 3.1415\n > y = base.truncsd( 3.14159, 1 )\n 3.0\n > y = base.truncsd( 12368.0, 2 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n" +base.uimul,"\nbase.uimul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.uimul( 10>>>0, 4>>>0 )\n 40\n\n" +base.uimuldw,"\nbase.uimuldw( [out,] a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.uimuldw( 1, 10 )\n [ 0, 10 ]\n\n" +base.uint32ToInt32,"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( {{alias:@stdlib/number/float64/base/to-uint32}}( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( {{alias:@stdlib/number/float64/base/to-uint32}}( 3 ) )\n 3\n\n" +base.vercos,"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n" +base.versin,"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n" +base.wrap,"\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n" +base.xlog1py,"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n" +base.xlogy,"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n" +base.zeta,"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n" +BERNDT_CPS_WAGES_1985,"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n" +bifurcate,"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n" +bifurcateBy,"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n" +bifurcateByAsync,"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n" +bifurcateIn,"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n" +bifurcateOwn,"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n" +binomialTest,"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n" +Buffer,"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n" +buffer2json,"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n The returned JSON object has the following properties:\n\n - type: value type\n - data: buffer data as a generic array\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/buffer/alloc-unsafe}}( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n" +capitalize,"\ncapitalize( str )\n Capitalizes the first character in a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n" +capitalizeKeys,"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n" +CATALAN,"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n" +CBRT_EPS,"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n" +chdir,"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n" +chi2gof,"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can be expected frequencies, population probabilities\n summing to one, or a discrete probability distribution name to test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: Array\n Observation frequencies.\n\n y: Array|string\n Expected frequencies (or probabilities) or a discrete probability\n distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p )\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.print()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.print()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts )\n {...}\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = {{alias:@stdlib/random/base/poisson}}.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new {{alias:@stdlib/array/int32}}( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda )\n {...}\n\n" +circarray2iterator,"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n" +circularArrayStream,"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an "objectMode" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +CircularBuffer,"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n buf.clear: Function\n Clears the buffer.\n\n buf.count: integer\n Number of elements currently in the buffer.\n\n buf.full: boolean\n Boolean indicating whether the buffer is full.\n\n buf.iterator: Function\n Returns an iterator for iterating over a buffer. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that a\n returned iterator does **not** iterate over partially full buffers.\n\n buf.length: integer\n Buffer length (capacity).\n\n buf.push: Function\n Adds a value to the buffer. If the buffer is full, the method returns\n the removed value; otherwise, the method returns `undefined`.\n\n buf.toArray: Function\n Returns an array of buffer values.\n\n buf.toJSON: Function\n Serializes a circular buffer as JSON.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n" +CMUDICT,"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary\n - phones: manners of articulation for each sound\n - symbols: complete list of ARPABET symbols used by the dictionary\n - vp: verbal pronunciations of punctuation marks\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n" +complex,"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n" +Complex64,"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 4.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 8.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n" +COMPLEX64_NUM_BYTES,"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n" +Complex128,"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 8.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 16.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n" +COMPLEX128_NUM_BYTES,"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n" +compose,"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n" +composeAsync,"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n" +configdir,"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n" +conj,"\nconj( z )\n Returns the complex conjugate of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Complex\n Complex conjugate.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n" +constantFunction,"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n" +constantStream,"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an "objectMode" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +constructorName,"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n" +contains,"\ncontains( val, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `val` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `val` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does not distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n val: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n" +convertArray,"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n The function supports the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n arr: Array|TypedArray\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n" +convertArraySame,"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n The function supports input arrays having the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n x: Array|TypedArray\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new {{alias:@stdlib/array/float32}}( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n" +convertPath,"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\foo\\bar\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\foo\\bar\\beep.c', 'win32' )\n 'C:\\\\foo\\bar\\beep.c'\n > out = convertPath( 'C:\\\\foo\\bar\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\foo\\bar\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n" +copy,"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n" +copyBuffer,"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = {{alias:@stdlib/buffer/from-array}}( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n" +countBy,"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n" +countByAsync,"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { "even": 2, "odd": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { "even": 2, "odd": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { "even": 2, "odd": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { "even": 2, "odd": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { "even": 2, "odd": 2 }\n\n" +curry,"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n" +curryRight,"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n" +cwd,"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n" +DALE_CHALL_NEW,"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n\n Returns\n -------\n out: Array\n List of familiar English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n" +datasets,"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n" +dayOfQuarter,"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n" +dayOfYear,"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n" +daysInMonth,"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n" +daysInYear,"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n" +debugSinkStream,"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an "objectMode" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in "objectMode".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n" +debugStream,"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an "objectMode" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in "objectMode".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n" +deepEqual,"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: bool\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n" +deepGet,"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n" +deepHasOwnProp,"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for "own" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for "own" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n" +deepHasProp,"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n" +deepPluck,"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n" +deepSet,"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n" +defineMemoizedProperty,"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n" +defineProperties,"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n" +defineProperty,"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n" +dirname,"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n" +DoublyLinkedList,"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n "snapshot", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n" +doUntil,"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n" +doUntilAsync,"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n" +doUntilEach,"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n" +doUntilEachRight,"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n" +doWhile,"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n" +doWhileAsync,"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n" +doWhileEach,"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n" +doWhileEachRight,"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n" +E,"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n" +emptyStream,"\nemptyStream( [options] )\n Returns an "empty" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an "objectMode" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +endsWith,"\nendsWith( str, search[, len] )\n Tests if a `string` ends with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` ends with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n" +enumerableProperties,"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n" +enumerablePropertiesIn,"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n" +enumerablePropertySymbols,"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n" +enumerablePropertySymbolsIn,"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n" +ENV,"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n" +EPS,"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n" +error2json,"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n" +EULERGAMMA,"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n" +every,"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n" +everyBy,"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n" +everyByAsync,"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n" +everyByRight,"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n" +everyByRightAsync,"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n" +evil,"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `"use strict";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n" +exists,"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n" +expandContractions,"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\'t be able to get y\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\'t to be my fault, because, you know, I didn\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n" +extname,"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n" +fastmath.abs,"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n" +fastmath.acosh,"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n" +fastmath.ampbm,"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n" +fastmath.asinh,"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n" +fastmath.atanh,"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n" +fastmath.hypot,"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n" +fastmath.log2Uint32,"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n" +fastmath.max,"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n" +fastmath.min,"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n" +fastmath.powint,"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n" +fastmath.sqrtUint32,"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n" +FEMALE_FIRST_NAMES_EN,"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. "Moby Word II." .\n\n" +FIFO,"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the "oldest" queue value (i.e., the value which is "first-out").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n "snapshot", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the "newest" queue value (i.e., the value which is "last-out").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current "first-out" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n" +find,"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n" +flattenArray,"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: Array\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n" +flattenObject,"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n" +flignerTest,"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups })\n\n" +FLOAT16_CBRT_EPS,"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n" +FLOAT16_EPS,"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n" +FLOAT16_EXPONENT_BIAS,"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n" +FLOAT16_MAX,"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n" +FLOAT16_MAX_SAFE_INTEGER,"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n" +FLOAT16_MIN_SAFE_INTEGER,"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n" +FLOAT16_NINF,"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n" +FLOAT16_NUM_BYTES,"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n" +FLOAT16_PINF,"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n" +FLOAT16_PRECISION,"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n" +FLOAT16_SMALLEST_NORMAL,"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n" +FLOAT16_SMALLEST_SUBNORMAL,"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n" +FLOAT16_SQRT_EPS,"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n" +FLOAT32_CBRT_EPS,"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566601151848\n\n" +FLOAT32_EPS,"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n" +FLOAT32_EXPONENT_BIAS,"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n" +FLOAT32_MAX,"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n" +FLOAT32_MAX_SAFE_INTEGER,"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n" +FLOAT32_MIN_SAFE_INTEGER,"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n" +FLOAT32_NINF,"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n" +FLOAT32_NUM_BYTES,"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n" +FLOAT32_PINF,"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n" +FLOAT32_PRECISION,"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n" +FLOAT32_SMALLEST_NORMAL,"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n" +FLOAT32_SMALLEST_SUBNORMAL,"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n" +FLOAT32_SQRT_EPS,"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n" +Float32Array,"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/float64}}( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n" +FLOAT64_EXPONENT_BIAS,"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n" +FLOAT64_HIGH_WORD_EXPONENT_MASK,"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > {{alias:@stdlib/number/uint32/base/to-binary-string}}( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n" +FLOAT64_HIGH_WORD_SIGNIFICAND_MASK,"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > {{alias:@stdlib/number/uint32/base/to-binary-string}}( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n" +FLOAT64_MAX,"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n" +FLOAT64_MAX_BASE2_EXPONENT,"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n" +FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL,"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n" +FLOAT64_MAX_BASE10_EXPONENT,"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n" +FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL,"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n" +FLOAT64_MAX_LN,"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n" +FLOAT64_MAX_SAFE_FIBONACCI,"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n" +FLOAT64_MAX_SAFE_INTEGER,"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n" +FLOAT64_MAX_SAFE_LUCAS,"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n" +FLOAT64_MAX_SAFE_NTH_FIBONACCI,"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n" +FLOAT64_MAX_SAFE_NTH_LUCAS,"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n" +FLOAT64_MIN_BASE2_EXPONENT,"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n" +FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL,"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n" +FLOAT64_MIN_BASE10_EXPONENT,"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n" +FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL,"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n" +FLOAT64_MIN_LN,"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n" +FLOAT64_MIN_SAFE_INTEGER,"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n" +FLOAT64_NUM_BYTES,"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n" +FLOAT64_PRECISION,"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n" +FLOAT64_SMALLEST_NORMAL,"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n" +FLOAT64_SMALLEST_SUBNORMAL,"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n" +Float64Array,"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/float32}}( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n" +forEach,"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n" +forEachAsync,"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n" +forEachRight,"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n" +forEachRightAsync,"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n" +forIn,"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n" +forOwn,"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n" +FOURTH_PI,"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n" +FOURTH_ROOT_EPS,"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n" +FRB_SF_WAGE_RIGIDITY,"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. "Wage Rigidity." .\n\n" +fromCodePoint,"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n" +functionName,"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `"anonymous"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n" +functionSequence,"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n" +functionSequenceAsync,"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n" +GAMMA_LANCZOS_G,"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n" +getegid,"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n" +geteuid,"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n" +getgid,"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n" +getGlobal,"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n" +getPrototypeOf,"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n" +getuid,"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n" +GLAISHER,"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n" +group,"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n" +groupBy,"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n" +groupByAsync,"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { "true": [ 1000, 3000 ], "false": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { "true": [ 2, 0 ], "false": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { "true": [ [ 2, 1000 ], [ 0, 3000 ] ], "false": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { "true": [ 3000, 1000 ], "false": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { "true": [ 3000, 1000 ], "false": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { "true": [ 3000, 1000 ], "false": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { "true": [ 2000, 1000 ], "false": [ 1500 ] }\n\n" +groupIn,"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n" +groupOwn,"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n" +HALF_LN2,"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n" +HALF_PI,"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n" +HARRISON_BOSTON_HOUSE_PRICES,"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. "Hedonic housing prices and\n the demand for clean air." _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. "On the Harrison and Rubinfeld\n Data." _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n" +HARRISON_BOSTON_HOUSE_PRICES_CORRECTED,"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. "Hedonic housing prices and\n the demand for clean air." _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. "On the Harrison and Rubinfeld\n Data." _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n" +hasArrayBufferSupport,"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n" +hasAsyncAwaitSupport,"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n" +hasAsyncIteratorSymbolSupport,"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n" +hasClassSupport,"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n" +hasDefinePropertiesSupport,"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n" +hasDefinePropertySupport,"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n" +hasFloat32ArraySupport,"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n" +hasFloat64ArraySupport,"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n" +hasFunctionNameSupport,"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n" +hasGeneratorSupport,"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n" +hasInt8ArraySupport,"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n" +hasInt16ArraySupport,"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n" +hasInt32ArraySupport,"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n" +hasIteratorSymbolSupport,"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n" +hasMapSupport,"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n" +hasNodeBufferSupport,"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n" +hasOwnProp,"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n" +hasProp,"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n" +hasProxySupport,"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n" +hasSetSupport,"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n" +hasSharedArrayBufferSupport,"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n" +hasSymbolSupport,"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n" +hasToStringTagSupport,"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n" +hasUint8ArraySupport,"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n" +hasUint8ClampedArraySupport,"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n" +hasUint16ArraySupport,"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n" +hasUint32ArraySupport,"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n" +hasWeakMapSupport,"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n" +hasWeakSetSupport,"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n" +hasWebAssemblySupport,"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n" +HERNDON_VENUS_SEMIDIAMETERS,"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. "Sample Criteria for Testing Outlying\n Observations." _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. "Procedures for Detecting Outlying Observations in\n Samples." _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. "Some Grubbs-Type Statistics\n for the Detection of Several Outliers." _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n" +homedir,"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n" +HOURS_IN_DAY,"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n" +HOURS_IN_WEEK,"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n" +hoursInMonth,"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n" +hoursInYear,"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n" +httpServer,"\nhttpServer( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n createServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var createServer = httpServer()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > createServer = httpServer( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > createServer = httpServer( opts )\n \n\n\ncreateServer( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var createServer = httpServer();\n > createServer( done );\n\n" +identity,"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n" +ifelse,"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n" +ifelseAsync,"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object\n - result: either `x` or `y`\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n" +ifthen,"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n" +ifthenAsync,"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion\n\n The predicate function callback accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n" +imag,"\nimag( z )\n Returns the imaginary component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n" +IMG_ACANTHUS_MOLLIS,"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_AIRPLANE_FROM_ABOVE,"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_ALLIUM_OREOPHILUM,"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_BLACK_CANYON,"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_DUST_BOWL_HOME,"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_FRENCH_ALPINE_LANDSCAPE,"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_LOCOMOTION_HOUSE_CAT,"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_LOCOMOTION_NUDE_MALE,"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_MARCH_PASTORAL,"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_NAGASAKI_BOATS,"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +incrapcorr,"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n" +incrcount,"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n" +incrcovariance,"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n" +incrcovmat,"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n" +incrcv,"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n" +increwmean,"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n" +increwstdev,"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n" +increwvariance,"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n" +incrgmean,"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n" +incrgrubbs,"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( {{alias:@stdlib/random/base/normal}}( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. "Sample Criteria for Testing Outlying\n Observations." _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. "Procedures for Detecting Outlying Observations in\n Samples." _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n" +incrhmean,"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n" +incrkmeans,"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n" +incrkurtosis,"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n" +incrmaape,"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n" +incrmae,"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n" +incrmapcorr,"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n" +incrmape,"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n" +incrmax,"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n" +incrmaxabs,"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n" +incrmcovariance,"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n" +incrmcv,"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n" +incrmda,"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n" +incrme,"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n" +incrmean,"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n" +incrmeanabs,"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n" +incrmeanabs2,"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n" +incrmeanstdev,"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n" +incrmeanvar,"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n" +incrmgmean,"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n" +incrmgrubbs,"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( {{alias:@stdlib/random/base/normal}}( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. "Sample Criteria for Testing Outlying\n Observations." _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. "Procedures for Detecting Outlying Observations in\n Samples." _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n" +incrmhmean,"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n" +incrmidrange,"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n" +incrmin,"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n" +incrminabs,"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n" +incrminmax,"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n" +incrminmaxabs,"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n" +incrmmaape,"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n" +incrmmae,"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n" +incrmmape,"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n" +incrmmax,"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n" +incrmmaxabs,"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n" +incrmmda,"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n" +incrmme,"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n" +incrmmean,"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n" +incrmmeanabs,"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n" +incrmmeanabs2,"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n" +incrmmeanstdev,"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n" +incrmmeanvar,"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n" +incrmmidrange,"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n" +incrmmin,"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n" +incrmminabs,"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n" +incrmminmax,"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n" +incrmminmaxabs,"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n" +incrmmpe,"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n" +incrmmse,"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n" +incrmpcorr,"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n" +incrmpcorr2,"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n" +incrmpcorrdist,"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n" +incrmpe,"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n" +incrmprod,"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n" +incrmrange,"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n" +incrmrmse,"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n" +incrmrss,"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n" +incrmse,"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n" +incrmstdev,"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n" +incrmsum,"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n" +incrmsumabs,"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n" +incrmsumabs2,"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n" +incrmsummary,"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n" +incrmsumprod,"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n" +incrmvariance,"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n" +incrmvmr,"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n" +incrpcorr,"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n" +incrpcorr2,"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n" +incrpcorrdist,"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n" +incrpcorrdistmat,"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n" +incrpcorrmat,"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n" +incrprod,"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n" +incrrange,"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n" +incrrmse,"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n" +incrrss,"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n" +incrskewness,"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n" +incrspace,"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n" +incrstdev,"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n" +incrsum,"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n" +incrsumabs,"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n" +incrsumabs2,"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n" +incrsummary,"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n" +incrsumprod,"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n" +incrvariance,"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n" +incrvmr,"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n" +incrwmean,"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value\n - w: weight\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n" +ind2sub,"\nind2sub( [out,] shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'wrap', the function wraps around\n a linear index exceeding array dimensions using modulo arithmetic. If\n equal to 'clamp', the function sets a linear index exceeding array\n dimensions to either `0` (minimum linear index) or the maximum linear\n index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n // Provide an output array:\n > var out = new Array( d.length );\n > s = ind2sub( out, d, 17 )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n" +indexOf,"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n" +inherit,"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n" +inheritedEnumerableProperties,"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n" +inheritedEnumerablePropertySymbols,"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n" +inheritedKeys,"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n" +inheritedNonEnumerableProperties,"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n" +inheritedNonEnumerablePropertyNames,"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n" +inheritedNonEnumerablePropertySymbols,"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n" +inheritedProperties,"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n" +inheritedPropertyDescriptor,"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n" +inheritedPropertyDescriptors,"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n" +inheritedPropertyNames,"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n" +inheritedPropertySymbols,"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n" +inheritedWritableProperties,"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n" +inheritedWritablePropertyNames,"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n" +inheritedWritablePropertySymbols,"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n" +inmap,"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n" +inmapAsync,"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n" +inmapRight,"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n" +inmapRightAsync,"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n" +inspectSinkStream,"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an "objectMode" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in "objectMode".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n" +inspectStream,"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an "objectMode" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in "objectMode".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n" +instanceOf,"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n" +INT8_MAX,"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n" +INT8_MIN,"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n" +INT8_NUM_BYTES,"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n" +Int8Array,"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" +INT16_MAX,"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n" +INT16_MIN,"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n" +INT16_NUM_BYTES,"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n" +Int16Array,"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" +INT32_MAX,"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n" +INT32_MIN,"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n" +INT32_NUM_BYTES,"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n" +Int32Array,"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int16}}( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" +IS_BIG_ENDIAN,"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n" +IS_BROWSER,"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n" +IS_DARWIN,"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n" +IS_ELECTRON,"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n" +IS_ELECTRON_MAIN,"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n" +IS_ELECTRON_RENDERER,"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n" +IS_LITTLE_ENDIAN,"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n" +IS_NODE,"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n" +IS_WEB_WORKER,"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n" +IS_WINDOWS,"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n" +isAbsolutePath,"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\foo\\bar\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\foo\\bar\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\bar\\baz' )\n false\n\n" +isAccessorProperty,"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n" +isAccessorPropertyIn,"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n" +isAlphagram,"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n" +isAlphaNumeric,"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n" +isAnagram,"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n" +isArguments,"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n" +isArray,"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n" +isArrayArray,"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n" +isArrayBuffer,"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new {{alias:@stdlib/array/buffer}}( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n" +isArrayLength,"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n" +isArrayLike,"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n" +isArrayLikeObject,"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n" +isASCII,"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( {{alias:@stdlib/string/from-code-point}}( 130 ) )\n false\n\n" +isBetween,"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n" +isBetweenArray,"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n" +isBinaryString,"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n" +isBoolean,"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n" +isBooleanArray,"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n" +isBoxedPrimitive,"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n" +isBuffer,"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new {{alias:@stdlib/buffer/ctor}}( 'beep' ) )\n true\n > bool = isBuffer( new {{alias:@stdlib/buffer/ctor}}( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n" +isCapitalized,"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n" +isCentrosymmetricMatrix,"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 2, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n" +isCircular,"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n" +isCircularArray,"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n" +isCircularPlainObject,"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n" +isCollection,"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n" +isComplex,"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplex( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n" +isComplex64,"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n" +isComplex64Array,"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new {{alias:@stdlib/array/complex64}}( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n" +isComplex128,"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n" +isComplex128Array,"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new {{alias:@stdlib/array/complex128}}( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n" +isComplexLike,"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n" +isComplexTypedArray,"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new {{alias:@stdlib/array/complex64}}( 10 ) )\n true\n\n" +isConfigurableProperty,"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n" +isConfigurablePropertyIn,"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n" +isDataProperty,"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n" +isDataPropertyIn,"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n" +isDateObject,"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n" +isDigitString,"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n" +isEmailAddress,"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n" +isEmptyArray,"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n" +isEmptyObject,"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n" +isEmptyString,"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n" +isEnumerableProperty,"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n" +isEnumerablePropertyIn,"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n" +isError,"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n" +isEvalError,"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n" +isEven,"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n" +isFalsy,"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n" +isFalsyArray,"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n" +isFinite,"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n" +isFiniteArray,"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n" +isFloat32Array,"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new {{alias:@stdlib/array/float32}}( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n" +isFloat64Array,"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new {{alias:@stdlib/array/float64}}( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n" +isFunction,"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n" +isFunctionArray,"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n" +isGeneratorObject,"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n" +isGeneratorObjectLike,"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n" +isHexString,"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n" +isInfinite,"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n" +isInheritedProperty,"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n" +isInt8Array,"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n" +isInt16Array,"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new {{alias:@stdlib/array/int16}}( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n" +isInt32Array,"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new {{alias:@stdlib/array/int32}}( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n" +isInteger,"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n" +isIntegerArray,"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n" +isIterableLike,"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n" +isIteratorLike,"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n" +isJSON,"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{"a":5}' )\n true\n > bool = isJSON( '{a":5}' )\n false\n\n" +isLeapYear,"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n" +isLowercase,"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n" +isMatrixLike,"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n" +isMethod,"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n" +isMethodIn,"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n" +isNamedTypedTupleLike,"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = {{alias:@stdlib/utils/named-typed-tuple}}( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n" +isnan,"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n" +isNaNArray,"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n" +isNativeFunction,"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n" +isndarrayLike,"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n" +isNegativeInteger,"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n" +isNegativeIntegerArray,"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n" +isNegativeNumber,"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n" +isNegativeNumberArray,"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n" +isNegativeZero,"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n" +isNodeBuiltin,"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n" +isNodeDuplexStreamLike,"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n" +isNodeReadableStreamLike,"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n" +isNodeREPL,"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n" +isNodeStreamLike,"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n" +isNodeTransformStreamLike,"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n" +isNodeWritableStreamLike,"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n" +isNonConfigurableProperty,"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n" +isNonConfigurablePropertyIn,"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n" +isNonEnumerableProperty,"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n" +isNonEnumerablePropertyIn,"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n" +isNonNegativeInteger,"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n" +isNonNegativeIntegerArray,"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n" +isNonNegativeNumber,"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n" +isNonNegativeNumberArray,"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n" +isNonPositiveInteger,"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n" +isNonPositiveIntegerArray,"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n" +isNonPositiveNumber,"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n" +isNonPositiveNumberArray,"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n" +isNonSymmetricMatrix,"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n" +isNull,"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n" +isNullArray,"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n" +isNumber,"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n" +isNumberArray,"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n" +isNumericArray,"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n\n" +isObject,"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n" +isObjectArray,"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n" +isObjectLike,"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n" +isOdd,"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n" +isoWeeksInYear,"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n" +isPersymmetricMatrix,"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n" +isPlainObject,"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n" +isPlainObjectArray,"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n" +isPositiveInteger,"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n" +isPositiveIntegerArray,"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n" +isPositiveNumber,"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n" +isPositiveNumberArray,"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n" +isPositiveZero,"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n" +isPrimitive,"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n" +isPrimitiveArray,"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n" +isPRNGLike,"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( {{alias:@stdlib/random/base/randu}} )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n" +isProbability,"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n" +isProbabilityArray,"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n" +isPrototypeOf,"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > {{alias:@stdlib/utils/inherit}}( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n" +isRangeError,"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n" +isReadableProperty,"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n" +isReadablePropertyIn,"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n" +isReadOnlyProperty,"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n" +isReadOnlyPropertyIn,"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n" +isReadWriteProperty,"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n" +isReadWritePropertyIn,"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n" +isReferenceError,"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n" +isRegExp,"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n" +isRegExpString,"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n" +isRelativePath,"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\bar\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\bar\\baz' )\n true\n > bool = isRelativePath( 'C:\\foo\\..\\bar\\baz' )\n false\n\n" +isSafeInteger,"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is "safe" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n" +isSafeIntegerArray,"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is "safe" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n" +isSameValue,"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n" +isSameValueZero,"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n" +isSharedArrayBuffer,"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new {{alias:@stdlib/array/shared-buffer}}( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n" +isSkewCentrosymmetricMatrix,"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 2, 1, -1, -2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n" +isSkewPersymmetricMatrix,"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 0, 0, -1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n" +isSkewSymmetricMatrix,"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, -1, 1, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n" +isSquareMatrix,"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, 0, 0, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n" +isStrictEqual,"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n" +isString,"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n" +isStringArray,"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n" +isSymbol,"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n" +isSymbolArray,"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n" +isSymmetricMatrix,"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n" +isSyntaxError,"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n" +isTruthy,"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n" +isTruthyArray,"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n" +isTypedArray,"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n\n" +isTypedArrayLength,"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n" +isTypedArrayLike,"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new {{alias:@stdlib/array/int16}}() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n" +isTypeError,"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n" +isUint8Array,"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new {{alias:@stdlib/array/uint8}}( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n" +isUint8ClampedArray,"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new {{alias:@stdlib/array/uint8c}}( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n" +isUint16Array,"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new {{alias:@stdlib/array/uint16}}( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n" +isUint32Array,"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new {{alias:@stdlib/array/uint32}}( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n" +isUNCPath,"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\server\\share\\foo\\bar\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n" +isUndefined,"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n" +isUndefinedOrNull,"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n" +isUnityProbabilityArray,"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new {{alias:@stdlib/array/uint8}}( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n" +isUppercase,"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n" +isURI,"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n" +isURIError,"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n" +isVectorLike,"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n" +isWhitespace,"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space ("WSpace=Y","WS") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property "WSpace=Y" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n" +isWritableProperty,"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n" +isWritablePropertyIn,"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n" +isWriteOnlyProperty,"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n" +isWriteOnlyPropertyIn,"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n" +iterAdd,"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n" +iterAdvance,"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n" +iterAny,"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n" +iterAnyBy,"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n" +iterator2array,"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value\n - index: iterated value index (zero-based)\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( {{alias:@stdlib/random/iter/randu}}( opts ) )\n\n" +iterator2arrayview,"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = {{alias:@stdlib/random/iter/randu}}({ 'iter': 10 });\n > var out = new {{alias:@stdlib/array/float64}}( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n" +iterator2arrayviewRight,"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = {{alias:@stdlib/random/iter/randu}}({ 'iter': 10 });\n > var out = new {{alias:@stdlib/array/float64}}( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n" +iteratorStream,"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = {{alias:@stdlib/random/iter/randu}}( opts );\n > var s = iteratorStream( it );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an "objectMode" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = {{alias:@stdlib/random/iter/randu}}( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +IteratorSymbol,"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n" +iterawgn,"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterawln,"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterawun,"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterBartlettHannPulse,"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterBartlettPulse,"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterConcat,"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n" +iterConstant,"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n" +iterCosineWave,"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterCounter,"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( {{alias:@stdlib/random/iter/randu}}() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n" +itercugmean,"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n" +itercuhmean,"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n" +itercumax,"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n" +itercumaxabs,"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n" +itercumean,"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n" +itercumeanabs,"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n" +itercumeanabs2,"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n" +itercumidrange,"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n" +itercumin,"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n" +itercuminabs,"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n" +itercuprod,"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n" +itercurange,"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n" +itercusum,"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n" +itercusumabs,"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n" +itercusumabs2,"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n" +iterDedupe,"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n" +iterDedupeBy,"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value\n - sprev: previous source iterated value\n - dprev: previous downstream iterated value\n - index: source iteration index (zero-based)\n - acc: previous resolved value\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a "duplicate".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n" +iterDiracComb,"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n" +iterDivide,"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n" +iterEmpty,"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n" +iterEvery,"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n" +iterEveryBy,"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n" +iterFibonacci,"\niterFibonacci( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacci();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n" +iterFill,"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( {{alias:@stdlib/random/iter/randu}}(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n" +iterFilter,"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n" +iterFilterMap,"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n" +iterFirst,"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n" +iterFlatTopPulse,"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterFlow,"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it1 = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it1 = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n" +iterForEach,"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( {{alias:@stdlib/random/iter/randu}}(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +iterHannPulse,"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterHead,"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( {{alias:@stdlib/random/iter/randu}}(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +iterIntersection,"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value "uniqueness" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n" +iterIntersectionByHash,"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered "unique" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n" +iterLanczosPulse,"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterLast,"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n" +iterLength,"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n" +iterMap,"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( {{alias:@stdlib/random/iter/randu}}(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +iterMapN,"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values\n - index: iteration index (zero-based)\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n" +itermax,"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n" +itermaxabs,"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n" +itermean,"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n" +itermeanabs,"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n" +itermeanabs2,"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n" +itermidrange,"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n" +itermin,"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n" +iterminabs,"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n" +itermmax,"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n" +itermmaxabs,"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n" +itermmean,"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n" +itermmeanabs,"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n" +itermmeanabs2,"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n" +itermmidrange,"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n" +itermmin,"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n" +itermminabs,"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n" +iterMod,"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n" +itermprod,"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n" +itermrange,"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n" +itermsum,"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n" +itermsumabs,"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n" +itermsumabs2,"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n" +iterMultiply,"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n" +iterNone,"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n" +iterNoneBy,"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n" +iterNonFibonacci,"\niterNonFibonacci( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacci();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n" +iterNth,"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n" +iterPeriodicSinc,"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterPipeline,"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/iter/pipeline-thunk}}( {{alias:@stdlib/iter/head}}, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = {{alias:@stdlib/iter/pipeline-thunk}}( {{alias:@stdlib/iter/some-by}}, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( {{alias:@stdlib/random/iter/randu}}() )\n \n\n" +iterPop,"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n" +iterprod,"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n" +iterPulse,"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n" +iterPush,"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n" +iterrange,"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n" +iterReject,"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n" +iterReplicate,"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n" +iterReplicateBy,"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value\n - index: source iteration index (zero-based)\n - n: iteration index (zero-based)\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n" +iterSawtoothWave,"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterShift,"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n" +iterSineWave,"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterSlice,"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( {{alias:@stdlib/random/iter/randu}}(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +iterSome,"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n" +iterSomeBy,"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n" +iterSquareWave,"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n" +iterstdev,"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n" +iterSubtract,"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 5.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n" +itersum,"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n" +itersumabs,"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n" +itersumabs2,"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n" +iterThunk,"\niterThunk( iterFcn[, ...args] )\n Returns an iterator "thunk".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( {{alias:@stdlib/iter/some}}, 3 );\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n" +iterTriangleWave,"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" +iterUnion,"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value "uniqueness" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n" +iterUnique,"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value "uniqueness" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n" +iterUniqueBy,"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered "unique" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n" +iterUniqueByHash,"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered "unique" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n" +iterUnshift,"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n" +itervariance,"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n" +joinStream,"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an "objectMode" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in "objectMode".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n" +kde2d,"" +keyBy,"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n" +keyByRight,"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n" +keysIn,"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n" +kruskalTest,"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups })\n\n" +kstest,"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 4839 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = {{alias:@stdlib/random/base/uniform}}.factory( 0.0, 1.0, { 'seed': 8798 })\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 })\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = {{alias:@stdlib/random/base/uniform}}.factory( 0.0, 1.0, { 'seed': 8798 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' })\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' })\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true })\n { pValue: ~1, statistic: 0.1, ... }\n\n" +LinkedList,"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n "snapshot", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n" +linspace,"\nlinspace( start, stop[, length] )\n Generates a linearly spaced numeric array.\n\n If a `length` is not provided, the default output array length is `100`.\n\n The output array is guaranteed to include the `start` and `stop` values.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Last array value.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = linspace( 0, 100, 6 )\n [ 0, 20, 40, 60, 80, 100 ]\n\n" +LIU_NEGATIVE_OPINION_WORDS_EN,"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. "Mining and Summarizing Customer\n Reviews." In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. "Opinion Observer:\n Analyzing and Comparing Opinions on the Web." In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n" +LIU_POSITIVE_OPINION_WORDS_EN,"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n" +LN_HALF,"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n" +LN_PI,"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n" +LN_SQRT_TWO_PI,"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n" +LN_TWO_PI,"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n" +LN2,"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n" +LN10,"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n" +LOG2E,"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n" +LOG10E,"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n" +logspace,"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n" +lowercase,"\nlowercase( str )\n Converts a `string` to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n" +lowercaseKeys,"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n" +lowess,"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new {{alias:@stdlib/array/float64}}( 100 );\n > var y = new {{alias:@stdlib/array/float64}}( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*{{alias:@stdlib/random/base/randn}}() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = {{alias:@stdlib/plot/ctor}}( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n" +lpad,"\nlpad( str, len[, pad] )\n Left pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n" +ltrim,"\nltrim( str )\n Trims whitespace from the beginning of a `string`.\n\n "Whitespace" is defined as the following characters:\n\n - \f\n - \n\n - \r\n - \t\n - \v\n - \u0020\n - \u00a0\n - \u1680\n - \u2000-\u200a\n - \u2028\n - \u2029\n - \u202f\n - \u205f\n - \u3000\n - \ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \r\n\t Beep \t\t\n ' )\n 'Beep \t\t\n '\n\n" +MALE_FIRST_NAMES_EN,"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n" +mapFun,"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n" +mapFunAsync,"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - `index`: invocation index (starting from zero)\n - `next`: callback to be invoked upon function completion\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n" +mapKeys,"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n" +mapKeysAsync,"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `key`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `key`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `key`\n - `value`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `key`: transformed key\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n" +mapValues,"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n" +mapValuesAsync,"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `value`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `value`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `value`\n - `key`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `value`: transformed value\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n" +MAX_ARRAY_LENGTH,"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n" +MAX_TYPED_ARRAY_LENGTH,"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n" +memoize,"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n" +merge,"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n" +MILLISECONDS_IN_DAY,"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n" +MILLISECONDS_IN_HOUR,"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n" +MILLISECONDS_IN_MINUTE,"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n" +MILLISECONDS_IN_SECOND,"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n" +MILLISECONDS_IN_WEEK,"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n" +MINARD_NAPOLEONS_MARCH,"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size\n - cities: cities\n - labels: map labels\n - temperature: temperature during the army's return from Russia\n - rivers: river data\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var river = data.river\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n" +MINUTES_IN_DAY,"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n" +MINUTES_IN_HOUR,"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n" +MINUTES_IN_WEEK,"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n" +minutesInMonth,"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n" +minutesInYear,"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n" +MOBY_DICK,"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier)\n - title: chapter title (if available; otherwise, empty)\n - text: chapter text\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n" +MONTH_NAMES_EN,"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n" +MONTHS_IN_YEAR,"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n" +moveProperty,"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n" +namedtypedtuple,"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( {{alias:@stdlib/array/float64}}[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...[, elementN]]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element: number\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n" +nativeClass,"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n" +ndarray,"\nndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarray( 'generic', 2 )\n \n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n" +ndarrayCastingModes,"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types\n - 'equiv': allow casting between identical and byte swapped types\n - 'safe': only allow "safe" casts\n - 'same-kind': allow "safe" casts and casts within the same kind (e.g.,\n between signed integers or between floats)\n - 'unsafe': allow casting between all types (including between integers and\n floats)\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'same-kind', 'unsafe' ]\n\n" +ndarrayDataTypes,"\nndarrayDataTypes()\n Returns a list of ndarray data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n \n\n" +ndarrayIndexModes,"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'clamp', 'wrap' ]\n\n" +ndarrayMemoized,"\nndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarrayMemoized( 'generic', 2 )\n \n > var f = ndarrayMemoized( 'generic', 2 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n" +ndarrayMinDataType,"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest "kind" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n" +ndarrayNextDataType,"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n" +ndarrayOrders,"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n" +ndarrayPromotionRules,"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest "kind" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n ndarray data type.\n\n dtype2: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n" +ndarraySafeCasts,"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n" +ndarraySameKindCasts,"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same "kind".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same "kind".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n" +NIGHTINGALES_ROSE,"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son. .\n\n" +NINF,"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n" +NODE_VERSION,"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n" +none,"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n" +noneBy,"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n" +noneByAsync,"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n" +noneByRight,"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n" +noneByRightAsync,"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n" +nonEnumerableProperties,"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n" +nonEnumerablePropertiesIn,"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n" +nonEnumerablePropertyNames,"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n" +nonEnumerablePropertyNamesIn,"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n" +nonEnumerablePropertySymbols,"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n" +nonEnumerablePropertySymbolsIn,"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n" +noop,"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n" +now,"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n" +NUM_CPUS,"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n" +Number,"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n" +objectEntries,"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n" +objectEntriesIn,"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n" +objectFromEntries,"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n" +objectInverse,"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n" +objectInverseBy,"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n" +objectKeys,"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n" +objectValues,"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n" +objectValuesIn,"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n" +omit,"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n" +omitBy,"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n" +openURL,"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n" +PACE_BOSTON_HOUSE_PRICES,"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number\n - town: town name\n - town_id: town identifier\n - tract: tract identifier\n - lon: longitude\n - lat: latitude\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. "Hedonic housing prices and\n the demand for clean air." _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. "On the Harrison and Rubinfeld\n Data." _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. "Using the Spatial\n Configuration of the Data to Improve Estimation." _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n" +pad,"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' })\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' })\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n" +papply,"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n" +papplyRight,"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n" +parallel,"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n Examples\n --------\n > function done( error ) { if ( error ) { throw error; } };\n > var files = [ './a.js', './b.js' ];\n > parallel( files, done );\n\n // Specify the number of workers:\n > var opts = { 'workers': 8 };\n > parallel( files, opts, done );\n\n" +parseJSON,"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{"beep":"boop"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{"beep":"boop","a":"b"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n" +PATH_DELIMITER,"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\Windows\\system32;C:\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\Windows\system32', 'C:\\Windows' ]\n\n" +PATH_DELIMITER_POSIX,"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n" +PATH_DELIMITER_WIN32,"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\Windows\\system32;C:\\Windows;C:\\Program Files\\node\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\Windows\\system32', 'C:\\Windows', 'C:\\Program Files\\node\\' ]\n\n" +PATH_SEP,"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\bar\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n" +PATH_SEP_POSIX,"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n" +PATH_SEP_WIN32,"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\'\n > var parts = 'foo\\bar\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n" +pcorrtest,"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = {{alias:@stdlib/random/base/normal}}( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + {{alias:@stdlib/random/base/normal}}( 0.0,\n ... {{alias:@stdlib/math/base/special/sqrt}}( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n" +percentEncode,"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n" +PHI,"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n" +PI,"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n" +PI_SQUARED,"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n" +pick,"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n" +pickBy,"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n" +PINF,"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n" +pkg2alias,"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n\n" +pkg2related,"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n\n" +PLATFORM,"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n" +plot,"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n" +Plot,"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n" +pluck,"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n" +pop,"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n" +prepend,"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n" +properties,"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n" +propertiesIn,"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n" +propertyDescriptor,"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n" +propertyDescriptorIn,"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n" +propertyDescriptors,"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n" +propertyDescriptorsIn,"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n" +propertyNames,"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n" +propertyNamesIn,"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n" +propertySymbols,"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n" +propertySymbolsIn,"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n" +Proxy,"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following "traps" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n" +push,"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n" +quarterOfYear,"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n" +random.iterators.arcsine,"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.bernoulli,"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.beta,"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.betaprime,"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.binomial,"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.boxMuller,"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.cauchy,"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.chi,"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.chisquare,"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.cosine,"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.discreteUniform,"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.erlang,"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.exponential,"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.f,"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.frechet,"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.gamma,"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.geometric,"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.gumbel,"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.hypergeometric,"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.improvedZiggurat,"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.invgamma,"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.kumaraswamy,"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.laplace,"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.levy,"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.logistic,"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.lognormal,"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.minstd,"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the "randomness quality" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.minstdShuffle,"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the "randomness\n quality" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.mt19937,"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.negativeBinomial,"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.normal,"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.pareto1,"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.poisson,"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.randi,"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.randn,"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.randu,"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.rayleigh,"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.t,"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.triangular,"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.uniform,"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.iterators.weibull,"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" +random.streams.arcsine,"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.bernoulli,"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.beta,"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.betaprime,"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.binomial,"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.boxMuller,"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.cauchy,"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.chi,"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.chisquare,"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.cosine,"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.discreteUniform,"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.erlang,"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.exponential,"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.f,"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.gamma,"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.geometric,"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.gumbel,"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.improvedZiggurat,"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.invgamma,"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.kumaraswamy,"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.laplace,"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.levy,"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.logistic,"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.lognormal,"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.minstd,"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the "randomness quality" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.minstdShuffle,"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the "randomness\n quality" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.mt19937,"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.negativeBinomial,"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.normal,"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.pareto1,"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.poisson,"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.randi,"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.randn,"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.randu,"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an "objectMode" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.rayleigh,"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.t,"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.uniform,"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +random.streams.weibull,"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +ranks,"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n" +RE_BASENAME,"\nRE_BASENAME\n Regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_BASENAME.posix\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nRE_BASENAME.win32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n 'index.js'\n\n" +RE_BASENAME_POSIX,"\nRE_BASENAME_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n" +RE_BASENAME_WINDOWS,"\nRE_BASENAME_WINDOWS\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME_WINDOWS.exec( '\\foo\\bar\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\bar\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n" +RE_COLOR_HEXADECIMAL,"\nRE_COLOR_HEXADECIMAL\n Regular expression to match a hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.test( '000' )\n false\n > bool = RE_COLOR_HEXADECIMAL.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.shorthand\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'ffffff' )\n false\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.either\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.either.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( 'beep' )\n false\n\n" +RE_DECIMAL_NUMBER,"\nRE_DECIMAL_NUMBER\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var bool = RE_DECIMAL_NUMBER.test( '1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '-1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0' )\n false\n > bool = RE_DECIMAL_NUMBER.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = new RegExp( RE_DECIMAL_NUMBER.source, 'g' );\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\n" +RE_DIRNAME,"\nRE_DIRNAME\n Regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_DIRNAME.posix\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nRE_DIRNAME.win32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n" +RE_DIRNAME_POSIX,"\nRE_DIRNAME_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( './' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n" +RE_DIRNAME_WINDOWS,"\nRE_DIRNAME_WINDOWS\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_WINDOWS.exec( 'foo\\bar\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_WINDOWS.exec( '\\foo\\bar\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n" +RE_EOL,"\nRE_EOL\n Regular expression to match a newline character sequence: /\r?\n/.\n\n Examples\n --------\n > var bool = RE_EOL.test( '\n' )\n true\n > bool = RE_EOL.test( '\r\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n false\n\n" +RE_EXTENDED_LENGTH_PATH,"\nRE_EXTENDED_LENGTH_PATH\n Regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\?\`.\n\n Examples\n --------\n > var path = '\\\\?\\C:\\foo\\bar';\n > var bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = '\\\\?\\UNC\\server\\share';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = 'C:\\foo\\bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n\n" +RE_EXTNAME,"\nRE_EXTNAME\n Regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_EXTNAME.posix\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nRE_EXTNAME.win32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n '.js'\n\n" +RE_EXTNAME_POSIX,"\nRE_EXTNAME_POSIX\n Regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( '.' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( './' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n" +RE_EXTNAME_WINDOWS,"\nRE_EXTNAME_WINDOWS\n Regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_WINDOWS.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_WINDOWS.exec( '\\foo\\bar\\file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'beep\\boop.' )[ 1 ]\n '.'\n > ext = RE_EXTNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n" +RE_FILENAME,"\nRE_FILENAME\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_FILENAME.posix\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nRE_FILENAME.win32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\foo\\bar\\index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ 'C:\\foo\\bar\\index.js', 'C:', '\\', 'foo\\bar\\', 'index.js', '.js' ]\n\n" +RE_FILENAME_POSIX,"\nRE_FILENAME_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_POSIX.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_POSIX.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( './' ).slice()\n [ './', '', '.', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n" +RE_FILENAME_WINDOWS,"\nRE_FILENAME_WINDOWS\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_WINDOWS.exec( 'C:\\foo\\bar\\index.js' ).slice()\n [ 'C:\\foo\\bar\\index.js', 'C:', '\\', 'foo\\bar\\', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\foo\\bar\\.gitignore' ).slice()\n [ '\\foo\\bar\\.gitignore', '', '\\', 'foo\\bar\\', '.gitignore', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'foo\\file.pdf' ).slice()\n [ 'foo\\file.pdf', '', '', 'foo\\', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\foo\\bar\\file' ).slice()\n [ '\\foo\\bar\\file', '', '\\', 'foo\\bar\\', 'file', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( './' ).slice()\n [ './', '', '', '.', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n" +RE_FUNCTION_NAME,"\nRE_FUNCTION_NAME\n Regular expression to capture a function name.\n\n Examples\n --------\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n" +RE_NATIVE_FUNCTION,"\nRE_NATIVE_FUNCTION\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = RE_NATIVE_FUNCTION.test( Date.toString() )\n true\n > bool = RE_NATIVE_FUNCTION.test( (function noop() {}).toString() )\n false\n\n" +RE_REGEXP,"\nRE_REGEXP\n Regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Examples\n --------\n > var bool = RE_REGEXP.test( '/^beep$/' )\n true\n > bool = RE_REGEXP.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE_REGEXP.test( '/^\/([^\/]+)\/(.*)$/' )\n false\n > bool = RE_REGEXP.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n true\n\n" +RE_UNC_PATH,"\nRE_UNC_PATH\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\server\\share\\foo\\bar\\baz:a:b';\n > var bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar\\baz::b';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar\\baz:a';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar\\baz';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'beep boop \\\\server\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz:a:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz::';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz:a:b:c';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '//server/share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = './foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE_UNC_PATH.test( path )\n false\n\n" +RE_UTF16_SURROGATE_PAIR,"\nRE_UTF16_SURROGATE_PAIR\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var bool = RE_UTF16_SURROGATE_PAIR.test( 'abc\uD800\uDC00def' )\n true\n > bool = RE_UTF16_SURROGATE_PAIR.test( 'abcdef' )\n false\n\n" +RE_UTF16_UNPAIRED_SURROGATE,"\nRE_UTF16_UNPAIRED_SURROGATE\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var bool = RE_UTF16_UNPAIRED_SURROGATE.test( 'abc' )\n false\n > bool = RE_UTF16_UNPAIRED_SURROGATE.test( '\uD800' )\n true\n\n" +RE_WHITESPACE,"\nRE_WHITESPACE\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space ("WSpace=Y","WS")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property "WSpace=Y" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var bool = RE_WHITESPACE.test( '\n' )\n true\n > bool = RE_WHITESPACE.test( ' ' )\n true\n > bool = RE_WHITESPACE.test( 'a' )\n false\n\n" +readDir,"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n" +readFile,"\nreadFile( file[, options,] clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n" +readFileList,"\nreadFileList( filepaths[, options,] clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path\n - data: file contents as either a Buffer or string\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n" +readJSON,"\nreadJSON( file[, options,] clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n" +readWASM,"\nreadWASM( file, [options,] clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n" +real,"\nreal( z )\n Returns the real component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n" +realmax,"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n" +realmin,"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n" +reduce,"\nreduce( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) { return acc + v; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduce( arr, 0, sum )\n 6.0\n\n" +reduceAsync,"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n" +reduceRight,"\nreduceRight( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) {\n ... console.log( '%s: %d', acc, v );\n ... return acc + v;\n ... };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduceRight( arr, 0, sum );\n 2: 3.0\n 1: 2.0\n 0: 1.0\n > out\n 6.0\n\n" +reduceRightAsync,"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n" +reFromString,"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n" +reim,"\nreim( z )\n Returns the real and imaginary components of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n" +removeFirst,"\nremoveFirst( str )\n Removes the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n\n" +removeLast,"\nremoveLast( str )\n Removes the last character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n\n" +removePunctuation,"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' "\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: "A leader leads by example not by force."';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\'"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n" +removeUTF8BOM,"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\ufeffbeep' )\n 'beep'\n\n" +removeWords,"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n" +rename,"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n" +reorderArguments,"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n" +repeat,"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n" +replace,"\nreplace( str, search, newval )\n Replaces `search` occurrences with a replacement `string`.\n\n When provided a `string` as the `search` value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n" +rescape,"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\[A\\-Z\\]\\*'\n\n" +resolveParentPath,"\nresolveParentPath( path[, options,] clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n" +reverseArguments,"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n" +reverseString,"\nreverseString( str )\n Reverses a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n" +reviveBasePRNG,"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( {{alias:@stdlib/random/base/mt19937}} );\n > var r = {{alias:@stdlib/utils/parse-json}}( str, reviveBasePRNG )\n \n\n" +reviveBuffer,"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer)\n - data: buffer data as an array of integers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{"type":"Buffer","data":[5,3]}';\n > var buf = {{alias:@stdlib/utils/parse-json}}( str, reviveBuffer )\n [ 5, 3 ]\n\n" +reviveComplex,"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., "Complex128", "Complex64")\n - re: real component (number)\n - im: imaginary component (number)\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{"type":"Complex128","re":5,"im":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex )\n \n\n" +reviveComplex64,"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{"type":"Complex64","re":5,"im":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex64 )\n \n\n" +reviveComplex128,"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{"type":"Complex128","re":5,"im":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex128 )\n \n\n" +reviveError,"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{"type":"TypeError","message":"beep"}';\n > var err = JSON.parse( str, reviveError )\n \n\n" +reviveTypedArray,"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., "Float64Array", "Int8Array")\n - data: typed array data as an array of numbers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{"type":"Float64Array","data":[5,3]}';\n > var arr = {{alias:@stdlib/utils/parse-json}}( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n" +rpad,"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n" +rtrim,"\nrtrim( str )\n Trims whitespace from the end of a `string`.\n\n "Whitespace" is defined as the following characters:\n\n - \f\n - \n\n - \r\n - \t\n - \v\n - \u0020\n - \u00a0\n - \u1680\n - \u2000-\u200a\n - \u2028\n - \u2029\n - \u202f\n - \u205f\n - \u3000\n - \ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \t\t\n Beep \r\n\t ' )\n ' \t\t\n Beep'\n\n" +safeintmax,"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n" +safeintmin,"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n" +sample,"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 })\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 })\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 })\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false })\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs })\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false })\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 });\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 });\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n" +SAVOY_STOPWORDS_FIN,"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" +SAVOY_STOPWORDS_FR,"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" +SAVOY_STOPWORDS_GER,"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" +SAVOY_STOPWORDS_IT,"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" +SAVOY_STOPWORDS_POR,"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" +SAVOY_STOPWORDS_SP,"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" +SAVOY_STOPWORDS_SWE,"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" +SECONDS_IN_DAY,"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n" +SECONDS_IN_HOUR,"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n" +SECONDS_IN_MINUTE,"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n" +SECONDS_IN_WEEK,"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n" +secondsInMonth,"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n" +secondsInYear,"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n" +setConfigurableReadOnly,"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n" +setConfigurableReadOnlyAccessor,"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n" +setConfigurableReadWriteAccessor,"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n" +setConfigurableWriteOnlyAccessor,"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n" +setMemoizedReadOnly,"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n" +setNonEnumerableProperty,"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > {{alias:@stdlib/utils/keys}}( obj )\n []\n\n" +setNonEnumerableReadOnly,"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n" +setNonEnumerableReadOnlyAccessor,"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n" +setNonEnumerableReadWriteAccessor,"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n" +setNonEnumerableWriteOnlyAccessor,"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n" +setReadOnly,"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n" +setReadOnlyAccessor,"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n" +setReadWriteAccessor,"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n" +setWriteOnlyAccessor,"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n" +SharedArrayBuffer,"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n" +shift,"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n" +shuffle,"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' });\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' });\n > bool = ( arr === out )\n false\n\n" +sizeOf,"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - complex128: 128-bit complex numbers\n - complex64: 64-bit complex numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n" +some,"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n" +someBy,"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n" +someByAsync,"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n" +someByRight,"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n" +someByRightAsync,"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n" +SOTU,"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year\n - name: President name\n - party: the President's political party\n - text: speech text\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n" +SPACHE_REVISED,"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. "A New Readability Formula for Primary-Grade Reading\n Materials." *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. "Assessing Readability." *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. "Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure." *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. "The assessment of linguistic difficulty in\n reading material." In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n" +SPAM_ASSASSIN,"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group)\n - group: message group\n - checksum: object containing checksum info\n - text: message text (including headers)\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages)\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages)\n - hard-ham-1: harder to detect non-spam e-mails (250 messages)\n - spam-1: spam e-mails (500 messages)\n - spam-2: spam e-mails collected at a later date (1396 messages)\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5)\n - value: checksum value\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n" +SparklineBase,"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n" +sparsearray2iterator,"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n" +sparsearray2iteratorRight,"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n" +splitStream,"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\r?\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\nb\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\r?\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\nb\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an "objectMode" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\r?\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in "objectMode".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\nb\c' );\n > s.end();\n\n" +SQRT_EPS,"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n" +SQRT_HALF,"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n" +SQRT_HALF_PI,"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n" +SQRT_PHI,"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n" +SQRT_PI,"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n" +SQRT_THREE,"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n" +SQRT_TWO,"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n" +SQRT_TWO_PI,"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n" +Stack,"\nStack()\n Stack constructor.\n\n A stack is also referred to as a "last-in-first-out" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the "newest" stack value (i.e., the value which is "first-out").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n "snapshot", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the "oldest" stack value (i.e., the value which is "last-out").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current "first-out" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n" +startcase,"\nstartcase( str )\n Capitalizes the first letter of each word in an input `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n" +startsWith,"\nstartsWith( str, search[, position] )\n Tests if a `string` starts with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` starts with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n" +STOPWORDS_EN,"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n" +stridedarray2iterator,"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n" +stridedArrayStream,"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an "objectMode" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +string2buffer,"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n" +sub2ind,"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'wrap', the function wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n" +SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK,"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. "Labelled data collection for\n anomaly detection in wireless sensor networks." In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n" +SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK,"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. "Labelled data collection for\n anomaly detection in wireless sensor networks." In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n" +Symbol,"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n" +tabulate,"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n" +tabulateBy,"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n" +tabulateByAsync,"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n" +tic,"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n" +timeit,"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` options is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \'Something went wrong.\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n "iterations": 1000000,\n "repeats": 3,\n "min": [ 0, 135734733 ], // [seconds,nanoseconds]\n "elapsed": 0.135734733, // seconds\n "rate": 7367311.062526641, // iterations/second\n "times": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n" +tmpdir,"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n" +toc,"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = {{alias:@stdlib/time/tic}}();\n > var delta = toc( start )\n [ , ]\n\n" +tokenize,"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n" +transformStream,"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an "objectMode" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in "objectMode".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n" +trim,"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n "Whitespace" is defined as the following characters:\n\n - \f\n - \n\n - \r\n - \t\n - \v\n - \u0020\n - \u00a0\n - \u1680\n - \u2000-\u200a\n - \u2028\n - \u2029\n - \u202f\n - \u205f\n - \u3000\n - \ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \t\t\n Beep \r\n\t ' )\n 'Beep'\n\n" +trycatch,"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( {{alias:@stdlib/random/base/randu}}() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n" +trycatchAsync,"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - result: function result\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object\n - result: either the result of `x` or the provided argument `y`\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n" +tryFunction,"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n" +tryRequire,"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n" +trythen,"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( {{alias:@stdlib/random/base/randu}}() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n" +trythenAsync,"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n" +ttest,"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory( 0.0, 2.0, { 'seed': 5776 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = {{alias:@stdlib/random/base/normal}}.factory( 1.0, 2.0, { 'seed': 786 });\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n" +ttest2,"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' });\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' })\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n" +TWO_PI,"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n" +typedarray,"\ntypedarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n" +typedarray2json,"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type\n - data: typed array data as a generic array\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n" +typedarrayComplexCtors,"\ntypedarrayComplexCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayComplexCtors( 'complex64' )\n \n > ctor = typedarrayComplexCtors( 'float32' )\n null\n\n" +typedarrayComplexDataTypes,"\ntypedarrayComplexDataTypes()\n Returns a list of complex typed array data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = typedarrayComplexDataTypes()\n \n\n" +typedarrayCtors,"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n" +typedarrayDataTypes,"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n" +typedarraypool,"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n" +typemax,"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n" +typemin,"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n" +typeOf,"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new {{alias:@stdlib/array/int8}}( 10 ) )\n 'int8array'\n > t = typeOf( new {{alias:@stdlib/array/uint8}}( 10 ) )\n 'uint8array'\n > t = typeOf( new {{alias:@stdlib/array/uint8c}}( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new {{alias:@stdlib/array/int16}}( 10 ) )\n 'int16array'\n > t = typeOf( new {{alias:@stdlib/array/uint16}}( 10 ) )\n 'uint16array'\n > t = typeOf( new {{alias:@stdlib/array/int32}}( 10 ) )\n 'int32array'\n > t = typeOf( new {{alias:@stdlib/array/uint32}}( 10 ) )\n 'uint32array'\n > t = typeOf( new {{alias:@stdlib/array/float32}}( 10 ) )\n 'float32array'\n > t = typeOf( new {{alias:@stdlib/array/float64}}( 10 ) )\n 'float64array'\n > t = typeOf( new {{alias:@stdlib/array/buffer}}( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new {{alias:@stdlib/buffer/ctor}}( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n" +UINT8_MAX,"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n" +UINT8_NUM_BYTES,"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n" +Uint8Array,"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" +Uint8ClampedArray,"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" +UINT16_MAX,"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n" +UINT16_NUM_BYTES,"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n" +Uint16Array,"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" +UINT32_MAX,"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n" +UINT32_NUM_BYTES,"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n" +Uint32Array,"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" +umask,"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to "1", the corresponding initial file\n permission is disabled. If the mask contains a bit set to "0", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a "1" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where "classes" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n "symbols" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and "operator" may be one of\n\n - `+`: enable\n - `-`: disable\n - `=`: enable specified and disable unspecified permissions\n\n For example,\n\n - `u-w`: disable user write permissions\n - `u+w`: enable user write permissions\n - `u=w`: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates "all", which is the same as specifying "ugo". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n" +uncapitalize,"\nuncapitalize( str )\n Lowercases the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n" +uncapitalizeKeys,"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n" +uncurry,"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n" +uncurryRight,"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n" +UNICODE_MAX,"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n" +UNICODE_MAX_BMP,"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n" +UnicodeColumnChartSparkline,"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n" +UnicodeLineChartSparkline,"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n" +UnicodeSparkline,"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n" +UnicodeTristateChartSparkline,"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n" +UnicodeUpDownChartSparkline,"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n" +UnicodeWinLossChartSparkline,"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n" +unlink,"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n" +unshift,"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n" +until,"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n" +untilAsync,"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n" +untilEach,"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n" +untilEachRight,"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n" +unzip,"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n" +uppercase,"\nuppercase( str )\n Converts a `string` to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n" +uppercaseKeys,"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n" +US_STATES_ABBR,"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n" +US_STATES_CAPITALS,"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n" +US_STATES_CAPITALS_NAMES,"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n" +US_STATES_NAMES,"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n" +US_STATES_NAMES_CAPITALS,"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n" +utf16ToUTF8Array,"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n" +vartest,"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n" +waterfall,"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n" +whileAsync,"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n" +whileEach,"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n" +whileEachRight,"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n" +whilst,"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n" +writableProperties,"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n" +writablePropertiesIn,"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n" +writablePropertyNames,"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n" +writablePropertyNamesIn,"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n" +writablePropertySymbols,"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n" +writablePropertySymbolsIn,"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n" +writeFile,"\nwriteFile( file, data[, options,] clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n" +zip,"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n" +ztest,"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory( 0.0, 2.0, { 'seed': 212 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 });\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' })\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' })\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n" +ztest2,"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 })\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n" diff --git a/lib/node_modules/@stdlib/repl/help/data/data.json b/lib/node_modules/@stdlib/repl/help/data/data.json new file mode 100644 index 000000000000..d2944339f5e1 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/data/data.json @@ -0,0 +1 @@ +{"AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( '{{alias:@stdlib/math/base/special/sin}}' )\n '@stdlib/math/base/special/sin'\n\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( '{{alias:@stdlib/math/base/special/sin}}' )\n [...]\n\n","aliases":"\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n","ARCH":"\nARCH\n Operating system CPU architecture.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new {{alias:@stdlib/array/buffer}}( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n","arrayDataTypes":"\narrayDataTypes()\n Returns a list of array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n \n\n","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Array data type.\n\n dtype2: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups })\n\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( {{alias:@stdlib/constants/math/float64-pinf}}, {{alias:@stdlib/constants/math/float64-ninf}} )\n Infinity\n > d = base.absdiff( {{alias:@stdlib/constants/math/float64-pinf}}, {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n\n","base.absInt32":"\nbase.absInt32( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.absInt32( -1|0 )\n 1\n > v = base.absInt32( 2|0 )\n 2\n > v = base.absInt32( 0|0 )\n 0\n\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent (in radians).\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.0\n > y = base.asin( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( {{alias:@stdlib/constants/math/float64-ninf}} )\n -Infinity\n > y = base.asinh( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -{{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~-1.004\n > y = base.atan( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n","base.atan2":"\nbase.atan2( y, x )\n Evaluates the arctangent of the quotient of two numbers.\n\n Parameters\n ----------\n y: number\n Numerator.\n\n x: number\n Denominator.\n\n Returns\n -------\n out: number\n Arctangent of `y/x` (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.0\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.besselj0( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.besselj1( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.bessely0( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.bessely1( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n","base.cabs":"\nbase.cabs( re, im )\n Computes the absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( 5.0, 3.0 )\n ~5.831\n\n","base.cabs2":"\nbase.cabs2( re, im )\n Computes the squared absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( 5.0, 3.0 )\n 34.0\n\n","base.cadd":"\nbase.cadd( [out,] re1, im1, re2, im2 )\n Adds two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cadd( 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float32}}( 2 );\n > y = base.cadd( out, 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n > var bool = ( y === out )\n true\n\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n","base.cceil":"\nbase.cceil( [out,] re, im )\n Rounds a complex number toward positive infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceil( 5.5, 3.3 )\n [ 6.0, 4.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cceil( out, 5.5, 3.3 )\n [ 6.0, 4.0 ]\n > var bool = ( v === out )\n true\n\n","base.cceiln":"\nbase.cceiln( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward positive\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cceiln( out, 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n > var bool = ( v === out )\n true\n\n","base.ccis":"\nbase.ccis( [out,] re, im )\n Computes the cis function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.ccis( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > var y = base.ccis( 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.ccis( out, 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n","base.cdiv":"\nbase.cdiv( [out,] re1, im1, re2, im2 )\n Divides two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cdiv( -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cdiv( out, -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n","base.ceil":"\nbase.ceil( x )\n Rounds a numeric value toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n","base.ceilsd":"\nbase.ceilsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1 )\n 4.0\n > y = base.ceilsd( 12368.0, 2 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n","base.cexp":"\nbase.cexp( [out,] re, im )\n Computes the exponential function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cexp( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > y = base.cexp( 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cexp( out, 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n","base.cflipsign":"\nbase.cflipsign( [out,] re, im, y )\n Returns a complex number with the same magnitude as `z` and the sign of\n `y*z`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.cflipsign( -4.2, 5.5, -9 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cflipsign( out, -4.2, 5.5, 8 )\n [ -4.2, 5.5 ]\n > var bool = ( v === out )\n true\n\n","base.cfloor":"\nbase.cfloor( [out,] re, im )\n Rounds a complex number toward negative infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cfloor( 5.5, 3.3 )\n [ 5.0, 3.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cfloor( out, 5.5, 3.3 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n","base.cfloorn":"\nbase.cfloorn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward negative\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cfloorn( 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cfloorn( out, 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n > var bool = ( v === out )\n true\n\n","base.cinv":"\nbase.cinv( [out,] re, im )\n Computes the inverse of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cinv( 2.0, 4.0 )\n [ 0.1, -0.2 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cinv( out, 2.0, 4.0 )\n [ 0.1, -0.2 ]\n > var bool = ( v === out )\n true\n\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a value to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n","base.cmul":"\nbase.cmul( [out,] re1, im1, re2, im2 )\n Multiplies two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.cmul( 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cmul( out, 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n > var bool = ( v === out )\n true\n\n","base.cneg":"\nbase.cneg( [out,] re, im )\n Negates a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Negated components.\n\n Examples\n --------\n > var out = base.cneg( -4.2, 5.5 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cneg( out, -4.2, 5.5 )\n [ 4.2, -5.5 ]\n > var bool = ( v === out )\n true\n\n","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~0.707\n > y = base.cos( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~-0.293\n > y = base.cosm1( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n","base.cphase":"\nbase.cphase( re, im )\n Computes the argument of a complex number in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( 5.0, 3.0 )\n ~0.5404\n\n","base.cpolar":"\nbase.cpolar( [out,] re, im )\n Returns the absolute value and phase of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cpolar( out, 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n","base.cround":"\nbase.cround( [out,] re, im )\n Rounds a complex number to the nearest integer.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cround( 5.5, 3.3 )\n [ 6.0, 3.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cround( out, 5.5, 3.3 )\n [ 6.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n","base.croundn":"\nbase.croundn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.croundn( 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.croundn( out, 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n > var bool = ( v === out )\n true\n\n","base.csignum":"\nbase.csignum( [out,] re, im )\n Evaluates the signum function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.csignum( -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.csignum( out, -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n > var bool = ( v === out )\n true\n\n","base.csub":"\nbase.csub( [out,] re1, im1, re2, im2 )\n Subtracts two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.csub( 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.csub( out, 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n > var bool = ( v === out )\n true\n\n","base.dasum":"\nbase.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.dasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.dasum( N, x1, stride )\n 12.0\n\n\nbase.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n\nbase.dasum.wasm( [options] )\n Returns a memory managed function to compute the sum of absolute values.\n\n For an externally defined `Float64Array`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.dasum.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var bytes = wasm.malloc( N * 8 );\n\n // Create a Float64Array view:\n > var view = new {{alias:@stdlib/array/float64}}( bytes.buffer, bytes.byteOffset, N );\n\n // Copy data to the heap:\n > view.set( [ 1.0, -2.0, 3.0, -4.0, 5.0 ] );\n\n // Compute the sum of absolute values (passing in the heap buffer):\n > var s = wasm( N, bytes, 1 )\n 15.0\n\n // Free the memory:\n > wasm.free( bytes );\n\n","base.daxpy":"\nbase.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.daxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.daxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.daxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.wasm( [options] )\n Returns a memory managed function to multiply `x` by a constant `alpha` and\n add the result to `y`.\n\n For externally defined `Float64Arrays`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.daxpy.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var xbytes = wasm.malloc( N * 8 );\n > var ybytes = wasm.malloc( N * 8 );\n\n // Create Float64Array views:\n > var x = new {{alias:@stdlib/array/float64}}( xbytes.buffer, xbytes.byteOffset, N );\n > var y = new {{alias:@stdlib/array/float64}}( ybytes.buffer, ybytes.byteOffset, N );\n\n // Copy data to the heap:\n > x.set( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > y.set( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n\n // Multiply and add alpha:\n > var alpha = 5.0;\n > wasm( x.length, alpha, xbytes, 1, ybytes, 1 );\n > y\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Free the memory:\n > wasm.free( xbytes );\n > wasm.free( ybytes );\n\n","base.dcopy":"\nbase.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.dcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.dcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.dcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of a F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns a F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of a F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of a F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of a F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for a F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for a F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of a F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of a F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of a F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n > y = base.ellipe( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n > y = base.ellipk( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.erfc( {{alias:@stdlib/constants/math/float64-ninf}} )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e34 ) )\n 114\n > exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`, else behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.14, 10.0 )\n -3.14\n > z = base.flipsign( -3.14, -1.0 )\n 3.14\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.14, -0.0 )\n 3.14\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( 4294967295.0 ) )\n -1\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14 ) )\n 3\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n -3\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( NaN ) )\n 0\n > y = base.float32ToInt32( {{alias:@stdlib/constants/math/float32-pinf}} )\n 0\n > y = base.float32ToInt32( {{alias:@stdlib/constants/math/float32-ninf}} )\n 0\n","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( 4294967297.0 ) )\n 1\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14 ) )\n 3\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( NaN ) )\n 0\n > y = base.float32ToUint32( {{alias:@stdlib/constants/math/float32-pinf}} )\n 0\n > y = base.float32ToUint32( {{alias:@stdlib/constants/math/float32-ninf}} )\n 0\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0\n > y = base.float64ToInt32( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0\n","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0\n > y = base.float64ToUint32( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0\n","base.floor":"\nbase.floor( x )\n Rounds a numeric value toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward negative\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n","base.floorsd":"\nbase.floorsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5 )\n 3.1415\n > y = base.floorsd( 3.14159, 1 )\n 3.0\n > y = base.floorsd( 12368.0, 2 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n","base.fresnel":"\nbase.fresnel( [out,] x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.fresnel( out, 0.0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( {{alias:@stdlib/constants/math/float64-pinf}} )\n ~0.5\n > y = base.fresnelc( {{alias:@stdlib/constants/math/float64-ninf}} )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( {{alias:@stdlib/constants/math/float64-pinf}} )\n ~0.5\n > y = base.fresnels( {{alias:@stdlib/constants/math/float64-ninf}} )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n","base.frexp":"\nbase.frexp( [out,] x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, 0 ]\n > out = base.frexp( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var y = base.frexp( out, 4.0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n","base.fromWordf":"\nbase.fromWordf( x )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n","base.gasum":"\nbase.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.gasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.gasum( N, x1, stride )\n 12.0\n\n\nbase.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > sum = base.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n","base.gaxpy":"\nbase.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gaxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.gaxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gaxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n","base.gcopy":"\nbase.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.gcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n","base.imuldw":"\nbase.imuldw( [out,] a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( {{alias:@stdlib/number/float64/base/to-int32}}( -32 ) )\n 4294967264\n > y = base.int32ToUint32( {{alias:@stdlib/number/float64/base/to-int32}}( 3 ) )\n 3\n\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( {{alias:@stdlib/constants/math/float64-pinf}} )\n false\n > bool = base.isFinite( {{alias:@stdlib/constants/math/float64-ninf}} )\n false\n\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( {{alias:@stdlib/constants/math/float64-pinf}} )\n true\n > bool = base.isInfinite( {{alias:@stdlib/constants/math/float64-ninf}} )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a numeric value is a probability.\n\n A probability is defined as a numeric value on the closed interval `[0,1]`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kernelBetainc":"\nbase.kernelBetainc( [out,] x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.32, 1.6 ]\n\n > out = new Array( 2 );\n > var v = base.kernelBetainc( out, 0.2, 1.0, 2.0, true, true )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( {{alias:@stdlib/constants/math/float64-pinf}}, 11 )\n Infinity\n > x = base.ldexp( {{alias:@stdlib/constants/math/float64-ninf}}, -118 )\n -Infinity\n\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of `x`.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n","base.max":"\nbase.max( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n","base.maxabs":"\nbase.maxabs( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n","base.min":"\nbase.min( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n","base.minabs":"\nbase.minabs( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n","base.minmax":"\nbase.minmax( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmax( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmax( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n","base.minmaxabs":"\nbase.minmaxabs( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabs( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmaxabs( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n","base.modf":"\nbase.modf( [out,] x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n parts: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, +0.0 ]\n > parts = base.modf( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > parts = base.modf( out, 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n\n","base.ndarray":"\nbase.ndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarray( 'float64', 3 )\n \n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n","base.ndarrayMemoized":"\nbase.ndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarrayMemoized( 'float64', 3 )\n \n > var f = base.ndarrayMemoized( 'float64', 3 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n","base.normalize":"\nbase.normalize( [out,] x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*{{alias:@stdlib/math/base/special/pow}}(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, 0 ]\n > out = base.normalize( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.normalize( out, 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > bool = ( v === out )\n true\n\n","base.normalizef":"\nbase.normalizef( [out,] x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( {{alias:@stdlib/number/float64/base/to-float32}}( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*{{alias:@stdlib/math/base/special/pow}}(2,exp) === {{alias:@stdlib/number/float64/base/to-float32}}(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( {{alias:@stdlib/constants/math/float32-pinf}} )\n [ Infinity, 0 ]\n > out = base.normalizef( {{alias:@stdlib/constants/math/float32-ninf}} )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float32}}( 2 );\n > var v = base.normalizef( out, {{alias:@stdlib/number/float64/base/to-float32}}( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( {{alias:@stdlib/constants/math/float64-pi}}, 5.0 )\n ~306.0197\n > y = base.pow( {{alias:@stdlib/constants/math/float64-pi}}, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( {{alias:@stdlib/constants/math/float64-pi}}, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n 90.0\n > d = base.rad2deg( -{{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( {{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n 29.999999999999996\n\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[1, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 1\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function\n returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = {{alias:@stdlib/math/base/special/abs}}( x );\n ... y = {{alias:@stdlib/math/base/special/abs}}( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * {{alias:@stdlib/constants/math/float64-eps}};\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = new Array( 2 );\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( y )\n '00000000000000000000011000000000'\n\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( y )\n '00000000010000000000000000000000'\n\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n","base.sasum":"\nbase.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.sasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.sasum( N, x1, stride )\n 12.0\n\n\nbase.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n","base.saxpy":"\nbase.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.saxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.saxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.saxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n","base.scopy":"\nbase.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.scopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.scopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.scopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( {{alias:@stdlib/constants/math/float64-pinf}}, high )\n 1.0\n\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( {{alias:@stdlib/constants/math/float64-pinf}}, low )\n NaN\n > y = base.setLowWord( {{alias:@stdlib/constants/math/float64-ninf}}, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n","base.sici":"\nbase.sici( [out,] x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > y = base.sici( out, 3.0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n\n","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( {{alias:@stdlib/number/float64/base/to-float32}}( 4.0 ) )\n false\n > bool = base.signbitf( {{alias:@stdlib/number/float64/base/to-float32}}( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e34 ) )\n 4293751\n > s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e-34 ) )\n 5288021\n > s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.0\n > y = base.sin( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n","base.sincos":"\nbase.sincos( [out,] x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.sincos( out, 0.0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n","base.sincospi":"\nbase.sincospi( [out,] x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.sincospi( out, 0.0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n","base.spence":"\nbase.spence( x )\n Evaluates Spence’s function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -{{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~-1.0\n > y = base.tan( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-pi}} )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-pinf}} )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-ninf}} )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( {{alias:@stdlib/constants/math/float64-pi}} ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/constants/math/float32-pinf}} )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/constants/math/float32-ninf}} )\n '11111111100000000000000000000000'\n\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint8}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint16}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint32}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = {{alias:@stdlib/number/float64/base/to-float32}}( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n","base.toWords":"\nbase.toWords( [out,] x )\n Splits a floating-point number into a higher order word (unsigned 32-bit\n integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/uint32}}( 2 );\n > w = base.toWords( out, 3.14e201 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n","base.trunc":"\nbase.trunc( x )\n Rounds a numeric value toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n","base.truncsd":"\nbase.truncsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5 )\n 3.1415\n > y = base.truncsd( 3.14159, 1 )\n 3.0\n > y = base.truncsd( 12368.0, 2 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n","base.uimul":"\nbase.uimul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.uimul( 10>>>0, 4>>>0 )\n 40\n\n","base.uimuldw":"\nbase.uimuldw( [out,] a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.uimuldw( 1, 10 )\n [ 0, 10 ]\n\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( {{alias:@stdlib/number/float64/base/to-uint32}}( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( {{alias:@stdlib/number/float64/base/to-uint32}}( 3 ) )\n 3\n\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n The returned JSON object has the following properties:\n\n - type: value type\n - data: buffer data as a generic array\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/buffer/alloc-unsafe}}( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can be expected frequencies, population probabilities\n summing to one, or a discrete probability distribution name to test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: Array\n Observation frequencies.\n\n y: Array|string\n Expected frequencies (or probabilities) or a discrete probability\n distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p )\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.print()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.print()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts )\n {...}\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = {{alias:@stdlib/random/base/poisson}}.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new {{alias:@stdlib/array/int32}}( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda )\n {...}\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n buf.clear: Function\n Clears the buffer.\n\n buf.count: integer\n Number of elements currently in the buffer.\n\n buf.full: boolean\n Boolean indicating whether the buffer is full.\n\n buf.iterator: Function\n Returns an iterator for iterating over a buffer. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that a\n returned iterator does **not** iterate over partially full buffers.\n\n buf.length: integer\n Buffer length (capacity).\n\n buf.push: Function\n Adds a value to the buffer. If the buffer is full, the method returns\n the removed value; otherwise, the method returns `undefined`.\n\n buf.toArray: Function\n Returns an array of buffer values.\n\n buf.toJSON: Function\n Serializes a circular buffer as JSON.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary\n - phones: manners of articulation for each sound\n - symbols: complete list of ARPABET symbols used by the dictionary\n - vp: verbal pronunciations of punctuation marks\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 4.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 8.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 8.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 16.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n","conj":"\nconj( z )\n Returns the complex conjugate of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Complex\n Complex conjugate.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n","contains":"\ncontains( val, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `val` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `val` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does not distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n val: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n The function supports the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n arr: Array|TypedArray\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n The function supports input arrays having the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n x: Array|TypedArray\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new {{alias:@stdlib/array/float32}}( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = {{alias:@stdlib/buffer/from-array}}( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n\n Returns\n -------\n out: Array\n List of familiar English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: bool\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","endsWith":"\nendsWith( str, search[, len] )\n Tests if a `string` ends with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` ends with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: Array\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups })\n\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566601151848\n\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/float64}}( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > {{alias:@stdlib/number/uint32/base/to-binary-string}}( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > {{alias:@stdlib/number/uint32/base/to-binary-string}}( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/float32}}( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n createServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var createServer = httpServer()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > createServer = httpServer( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > createServer = httpServer( opts )\n \n\n\ncreateServer( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var createServer = httpServer();\n > createServer( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object\n - result: either `x` or `y`\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion\n\n The predicate function callback accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n","imag":"\nimag( z )\n Returns the imaginary component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( {{alias:@stdlib/random/base/normal}}( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( {{alias:@stdlib/random/base/normal}}( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value\n - w: weight\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n","ind2sub":"\nind2sub( [out,] shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'wrap', the function wraps around\n a linear index exceeding array dimensions using modulo arithmetic. If\n equal to 'clamp', the function sets a linear index exceeding array\n dimensions to either `0` (minimum linear index) or the maximum linear\n index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n // Provide an output array:\n > var out = new Array( d.length );\n > s = ind2sub( out, d, 17 )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int16}}( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new {{alias:@stdlib/array/buffer}}( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( {{alias:@stdlib/string/from-code-point}}( 130 ) )\n false\n\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new {{alias:@stdlib/buffer/ctor}}( 'beep' ) )\n true\n > bool = isBuffer( new {{alias:@stdlib/buffer/ctor}}( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 2, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplex( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new {{alias:@stdlib/array/complex64}}( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new {{alias:@stdlib/array/complex128}}( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new {{alias:@stdlib/array/complex64}}( 10 ) )\n true\n\n","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new {{alias:@stdlib/array/float32}}( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new {{alias:@stdlib/array/float64}}( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new {{alias:@stdlib/array/int16}}( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new {{alias:@stdlib/array/int32}}( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = {{alias:@stdlib/utils/named-typed-tuple}}( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( {{alias:@stdlib/random/base/randu}} )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > {{alias:@stdlib/utils/inherit}}( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new {{alias:@stdlib/array/shared-buffer}}( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 2, 1, -1, -2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 0, 0, -1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, -1, 1, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, 0, 0, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new {{alias:@stdlib/array/int16}}() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new {{alias:@stdlib/array/uint8}}( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new {{alias:@stdlib/array/uint8c}}( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new {{alias:@stdlib/array/uint16}}( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new {{alias:@stdlib/array/uint32}}( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new {{alias:@stdlib/array/uint8}}( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value\n - index: iterated value index (zero-based)\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( {{alias:@stdlib/random/iter/randu}}( opts ) )\n\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = {{alias:@stdlib/random/iter/randu}}({ 'iter': 10 });\n > var out = new {{alias:@stdlib/array/float64}}( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = {{alias:@stdlib/random/iter/randu}}({ 'iter': 10 });\n > var out = new {{alias:@stdlib/array/float64}}( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = {{alias:@stdlib/random/iter/randu}}( opts );\n > var s = iteratorStream( it );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = {{alias:@stdlib/random/iter/randu}}( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( {{alias:@stdlib/random/iter/randu}}() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value\n - sprev: previous source iterated value\n - dprev: previous downstream iterated value\n - index: source iteration index (zero-based)\n - acc: previous resolved value\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n","iterFibonacci":"\niterFibonacci( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacci();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( {{alias:@stdlib/random/iter/randu}}(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it1 = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it1 = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( {{alias:@stdlib/random/iter/randu}}(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( {{alias:@stdlib/random/iter/randu}}(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( {{alias:@stdlib/random/iter/randu}}(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values\n - index: iteration index (zero-based)\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n","iterNonFibonacci":"\niterNonFibonacci( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacci();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/iter/pipeline-thunk}}( {{alias:@stdlib/iter/head}}, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = {{alias:@stdlib/iter/pipeline-thunk}}( {{alias:@stdlib/iter/some-by}}, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( {{alias:@stdlib/random/iter/randu}}() )\n \n\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value\n - index: source iteration index (zero-based)\n - n: iteration index (zero-based)\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( {{alias:@stdlib/random/iter/randu}}(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 5.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( {{alias:@stdlib/iter/some}}, 3 );\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n","kde2d":"","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups })\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 4839 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = {{alias:@stdlib/random/base/uniform}}.factory( 0.0, 1.0, { 'seed': 8798 })\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 })\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = {{alias:@stdlib/random/base/uniform}}.factory( 0.0, 1.0, { 'seed': 8798 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' })\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' })\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true })\n { pValue: ~1, statistic: 0.1, ... }\n\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n","linspace":"\nlinspace( start, stop[, length] )\n Generates a linearly spaced numeric array.\n\n If a `length` is not provided, the default output array length is `100`.\n\n The output array is guaranteed to include the `start` and `stop` values.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Last array value.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = linspace( 0, 100, 6 )\n [ 0, 20, 40, 60, 80, 100 ]\n\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n","lowercase":"\nlowercase( str )\n Converts a `string` to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new {{alias:@stdlib/array/float64}}( 100 );\n > var y = new {{alias:@stdlib/array/float64}}( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*{{alias:@stdlib/random/base/randn}}() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = {{alias:@stdlib/plot/ctor}}( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - `index`: invocation index (starting from zero)\n - `next`: callback to be invoked upon function completion\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `key`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `key`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `key`\n - `value`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `key`: transformed key\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `value`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `value`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `value`\n - `key`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `value`: transformed value\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size\n - cities: cities\n - labels: map labels\n - temperature: temperature during the army's return from Russia\n - rivers: river data\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var river = data.river\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier)\n - title: chapter title (if available; otherwise, empty)\n - text: chapter text\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( {{alias:@stdlib/array/float64}}[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...[, elementN]]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element: number\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n","ndarray":"\nndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarray( 'generic', 2 )\n \n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types\n - 'equiv': allow casting between identical and byte swapped types\n - 'safe': only allow \"safe\" casts\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats)\n - 'unsafe': allow casting between all types (including between integers and\n floats)\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'same-kind', 'unsafe' ]\n\n","ndarrayDataTypes":"\nndarrayDataTypes()\n Returns a list of ndarray data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n \n\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'clamp', 'wrap' ]\n\n","ndarrayMemoized":"\nndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarrayMemoized( 'generic', 2 )\n \n > var f = ndarrayMemoized( 'generic', 2 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n ndarray data type.\n\n dtype2: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son. .\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number\n - town: town name\n - town_id: town identifier\n - tract: tract identifier\n - lon: longitude\n - lat: latitude\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' })\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' })\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n Examples\n --------\n > function done( error ) { if ( error ) { throw error; } };\n > var files = [ './a.js', './b.js' ];\n > parallel( files, done );\n\n // Specify the number of workers:\n > var opts = { 'workers': 8 };\n > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = {{alias:@stdlib/random/base/normal}}( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + {{alias:@stdlib/random/base/normal}}( 0.0,\n ... {{alias:@stdlib/math/base/special/sqrt}}( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","RE_BASENAME":"\nRE_BASENAME\n Regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_BASENAME.posix\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nRE_BASENAME.win32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n","RE_BASENAME_POSIX":"\nRE_BASENAME_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n","RE_BASENAME_WINDOWS":"\nRE_BASENAME_WINDOWS\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n","RE_COLOR_HEXADECIMAL":"\nRE_COLOR_HEXADECIMAL\n Regular expression to match a hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.test( '000' )\n false\n > bool = RE_COLOR_HEXADECIMAL.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.shorthand\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'ffffff' )\n false\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.either\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.either.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( 'beep' )\n false\n\n","RE_DECIMAL_NUMBER":"\nRE_DECIMAL_NUMBER\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var bool = RE_DECIMAL_NUMBER.test( '1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '-1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0' )\n false\n > bool = RE_DECIMAL_NUMBER.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = new RegExp( RE_DECIMAL_NUMBER.source, 'g' );\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\n","RE_DIRNAME":"\nRE_DIRNAME\n Regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_DIRNAME.posix\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nRE_DIRNAME.win32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\\\foo\\\\bar'\n\n","RE_DIRNAME_POSIX":"\nRE_DIRNAME_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( './' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n","RE_DIRNAME_WINDOWS":"\nRE_DIRNAME_WINDOWS\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\\\foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\\\foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n","RE_EOL":"\nRE_EOL\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\n","RE_EXTENDED_LENGTH_PATH":"\nRE_EXTENDED_LENGTH_PATH\n Regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Examples\n --------\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n\n","RE_EXTNAME":"\nRE_EXTNAME\n Regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_EXTNAME.posix\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nRE_EXTNAME.win32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n","RE_EXTNAME_POSIX":"\nRE_EXTNAME_POSIX\n Regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( '.' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( './' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n","RE_EXTNAME_WINDOWS":"\nRE_EXTNAME_WINDOWS\n Regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE_EXTNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n","RE_FILENAME":"\nRE_FILENAME\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_FILENAME.posix\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nRE_FILENAME.win32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n","RE_FILENAME_POSIX":"\nRE_FILENAME_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_POSIX.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_POSIX.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( './' ).slice()\n [ './', '', '.', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n","RE_FILENAME_WINDOWS":"\nRE_FILENAME_WINDOWS\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( './' ).slice()\n [ './', '', '', '.', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n","RE_FUNCTION_NAME":"\nRE_FUNCTION_NAME\n Regular expression to capture a function name.\n\n Examples\n --------\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n","RE_NATIVE_FUNCTION":"\nRE_NATIVE_FUNCTION\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = RE_NATIVE_FUNCTION.test( Date.toString() )\n true\n > bool = RE_NATIVE_FUNCTION.test( (function noop() {}).toString() )\n false\n\n","RE_REGEXP":"\nRE_REGEXP\n Regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Examples\n --------\n > var bool = RE_REGEXP.test( '/^beep$/' )\n true\n > bool = RE_REGEXP.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE_REGEXP.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE_REGEXP.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n","RE_UNC_PATH":"\nRE_UNC_PATH\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '//server/share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = './foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE_UNC_PATH.test( path )\n false\n\n","RE_UTF16_SURROGATE_PAIR":"\nRE_UTF16_SURROGATE_PAIR\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var bool = RE_UTF16_SURROGATE_PAIR.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE_UTF16_SURROGATE_PAIR.test( 'abcdef' )\n false\n\n","RE_UTF16_UNPAIRED_SURROGATE":"\nRE_UTF16_UNPAIRED_SURROGATE\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var bool = RE_UTF16_UNPAIRED_SURROGATE.test( 'abc' )\n false\n > bool = RE_UTF16_UNPAIRED_SURROGATE.test( '\\uD800' )\n true\n\n","RE_WHITESPACE":"\nRE_WHITESPACE\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var bool = RE_WHITESPACE.test( '\\n' )\n true\n > bool = RE_WHITESPACE.test( ' ' )\n true\n > bool = RE_WHITESPACE.test( 'a' )\n false\n\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n","readFile":"\nreadFile( file[, options,] clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n","readFileList":"\nreadFileList( filepaths[, options,] clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path\n - data: file contents as either a Buffer or string\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readJSON":"\nreadJSON( file[, options,] clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n","readWASM":"\nreadWASM( file, [options,] clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n","real":"\nreal( z )\n Returns the real component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n","reduce":"\nreduce( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) { return acc + v; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduce( arr, 0, sum )\n 6.0\n\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n","reduceRight":"\nreduceRight( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) {\n ... console.log( '%s: %d', acc, v );\n ... return acc + v;\n ... };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduceRight( arr, 0, sum );\n 2: 3.0\n 1: 2.0\n 0: 1.0\n > out\n 6.0\n\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reim":"\nreim( z )\n Returns the real and imaginary components of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n","removeFirst":"\nremoveFirst( str )\n Removes the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n\n","removeLast":"\nremoveLast( str )\n Removes the last character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n","replace":"\nreplace( str, search, newval )\n Replaces `search` occurrences with a replacement `string`.\n\n When provided a `string` as the `search` value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","resolveParentPath":"\nresolveParentPath( path[, options,] clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n","reverseString":"\nreverseString( str )\n Reverses a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( {{alias:@stdlib/random/base/mt19937}} );\n > var r = {{alias:@stdlib/utils/parse-json}}( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer)\n - data: buffer data as an array of integers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = {{alias:@stdlib/utils/parse-json}}( str, reviveBuffer )\n [ 5, 3 ]\n\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\")\n - re: real component (number)\n - im: imaginary component (number)\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex )\n \n\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex64 )\n \n\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex128 )\n \n\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\")\n - data: typed array data as an array of numbers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = {{alias:@stdlib/utils/parse-json}}( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 })\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 })\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 })\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false })\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs })\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false })\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 });\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 });\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > {{alias:@stdlib/utils/keys}}( obj )\n []\n\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' });\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' });\n > bool = ( arr === out )\n false\n\n","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - complex128: 128-bit complex numbers\n - complex64: 64-bit complex numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year\n - name: President name\n - party: the President's political party\n - text: speech text\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group)\n - group: message group\n - checksum: object containing checksum info\n - text: message text (including headers)\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages)\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages)\n - hard-ham-1: harder to detect non-spam e-mails (250 messages)\n - spam-1: spam e-mails (500 messages)\n - spam-2: spam e-mails collected at a later date (1396 messages)\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5)\n - value: checksum value\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a `string` starts with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` starts with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'wrap', the function wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` options is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = {{alias:@stdlib/time/tic}}();\n > var delta = toc( start )\n [ , ]\n\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( {{alias:@stdlib/random/base/randu}}() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - result: function result\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object\n - result: either the result of `x` or the provided argument `y`\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( {{alias:@stdlib/random/base/randu}}() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory( 0.0, 2.0, { 'seed': 5776 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = {{alias:@stdlib/random/base/normal}}.factory( 1.0, 2.0, { 'seed': 786 });\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' });\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' })\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type\n - data: typed array data as a generic array\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n","typedarrayComplexCtors":"\ntypedarrayComplexCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayComplexCtors( 'complex64' )\n \n > ctor = typedarrayComplexCtors( 'float32' )\n null\n\n","typedarrayComplexDataTypes":"\ntypedarrayComplexDataTypes()\n Returns a list of complex typed array data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = typedarrayComplexDataTypes()\n \n\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new {{alias:@stdlib/array/int8}}( 10 ) )\n 'int8array'\n > t = typeOf( new {{alias:@stdlib/array/uint8}}( 10 ) )\n 'uint8array'\n > t = typeOf( new {{alias:@stdlib/array/uint8c}}( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new {{alias:@stdlib/array/int16}}( 10 ) )\n 'int16array'\n > t = typeOf( new {{alias:@stdlib/array/uint16}}( 10 ) )\n 'uint16array'\n > t = typeOf( new {{alias:@stdlib/array/int32}}( 10 ) )\n 'int32array'\n > t = typeOf( new {{alias:@stdlib/array/uint32}}( 10 ) )\n 'uint32array'\n > t = typeOf( new {{alias:@stdlib/array/float32}}( 10 ) )\n 'float32array'\n > t = typeOf( new {{alias:@stdlib/array/float64}}( 10 ) )\n 'float64array'\n > t = typeOf( new {{alias:@stdlib/array/buffer}}( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new {{alias:@stdlib/buffer/ctor}}( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - `+`: enable\n - `-`: disable\n - `=`: enable specified and disable unspecified permissions\n\n For example,\n\n - `u-w`: disable user write permissions\n - `u+w`: enable user write permissions\n - `u=w`: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n","uppercase":"\nuppercase( str )\n Converts a `string` to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n","writeFile":"\nwriteFile( file, data[, options,] clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory( 0.0, 2.0, { 'seed': 212 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 });\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' })\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' })\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 })\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/help/datapackage.json b/lib/node_modules/@stdlib/repl/help/datapackage.json new file mode 100644 index 000000000000..a352c9174628 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/datapackage.json @@ -0,0 +1,60 @@ +{ + "name": "stdlib-help-text", + "version": "", + "title": "Standard Library Aliases and Help Texts", + "description": "A mapping between standard library aliases and help texts.", + "resources": [ + { + "name": "stdlib-help-text-json", + "title": "Standard Library Aliases and Help Texts", + "description": "A mapping between standard library aliases and help texts.", + "format": "json", + "mediatype": "application/json", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.json" + }, + { + "name": "stdlib-help-text-csv", + "title": "Standard Library Aliases and Help Texts", + "description": "A mapping between standard library aliases and help texts.", + "format": "csv", + "mediatype": "plain/csv", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.csv", + "schema": { + "fields": [ + { + "name": "alias", + "title": "Alias", + "description": "Alias.", + "type": "string", + "format": "default" + }, + { + "name": "text", + "title": "Help Text", + "description": "Help text.", + "type": "string", + "format": "default" + } + ] + } + } + ], + "sources": [], + "keywords": [ + "stdlib", + "namespace", + "aliases", + "help", + "text", + "txt", + "docs", + "documentation", + "repl", + "usage" + ], + "license": "PDDL-1.0 AND CC0-1.0" +} diff --git a/lib/node_modules/@stdlib/repl/help/docs/repl.txt b/lib/node_modules/@stdlib/repl/help/docs/repl.txt new file mode 100644 index 000000000000..e3279254ea9a --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/docs/repl.txt @@ -0,0 +1,21 @@ + +{{alias}}( alias ) + Returns the help text associated with a provided alias. + + Parameters + ---------- + alias: string + Alias. + + Returns + ------- + out: string|null + Help text. + + Examples + -------- + > var txt = {{alias}}( '{{alias:@stdlib/math/base/special/sin}}' ) + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/repl/help/docs/types/index.d.ts b/lib/node_modules/@stdlib/repl/help/docs/types/index.d.ts new file mode 100644 index 000000000000..f160fae3d849 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/docs/types/index.d.ts @@ -0,0 +1,35 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Returns help text associated with a specified alias. +* +* @param alias - alias +* @returns help text +* +* @example +* var txt = help( 'base.sin' ); +*/ +declare function help( alias: string ): string | null; + + +// EXPORTS // + +export = help; diff --git a/lib/node_modules/@stdlib/repl/help/docs/types/test.ts b/lib/node_modules/@stdlib/repl/help/docs/types/test.ts new file mode 100644 index 000000000000..4c8a6bd87784 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import help = require( './index' ); + + +// TESTS // + +// The function returns a string or null... +{ + help( 'base.sin' ); // $ExpectType string | null +} + +// The compiler throws an error if the function is not provided a string... +{ + help( 5 ); // $ExpectError + help( true ); // $ExpectError + help( false ); // $ExpectError + help( null ); // $ExpectError + help( undefined ); // $ExpectError + help( [] ); // $ExpectError + help( {} ); // $ExpectError + help( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + help( 'base.sin', 'beep' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/repl/help/docs/usage.txt b/lib/node_modules/@stdlib/repl/help/docs/usage.txt new file mode 100644 index 000000000000..8405d794390c --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/docs/usage.txt @@ -0,0 +1,8 @@ + +Usage: stdlib-help-text [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. + diff --git a/lib/node_modules/@stdlib/repl/help/etc/cli_opts.json b/lib/node_modules/@stdlib/repl/help/etc/cli_opts.json new file mode 100644 index 000000000000..92119c456962 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/etc/cli_opts.json @@ -0,0 +1,15 @@ +{ + "string": [], + "boolean": [ + "help", + "version" + ], + "alias": { + "help": [ + "h" + ], + "version": [ + "V" + ] + } +} diff --git a/lib/node_modules/@stdlib/repl/help/examples/index.js b/lib/node_modules/@stdlib/repl/help/examples/index.js index 9b69572f9a12..5ebfe66e6bc5 100644 --- a/lib/node_modules/@stdlib/repl/help/examples/index.js +++ b/lib/node_modules/@stdlib/repl/help/examples/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -18,8 +18,19 @@ 'use strict'; +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); var help = require( './../lib' ); -var db = help(); -console.log( db ); -// => {...} +var list; +var len; +var idx; +var i; + +list = aliases(); +len = list.length; + +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len-1 ); + console.log( help( list[ idx ] ) ); +} diff --git a/lib/node_modules/@stdlib/repl/help/lib/db.js b/lib/node_modules/@stdlib/repl/help/lib/db.js deleted file mode 100644 index 3676856ba4b1..000000000000 --- a/lib/node_modules/@stdlib/repl/help/lib/db.js +++ /dev/null @@ -1,1915 +0,0 @@ -/* eslint-disable quotes, max-lines */ - -/** -* @license Apache-2.0 -* -* Copyright (c) 2019 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* -* This file is generated by scripts/build.js. -*/ -'use strict'; - -var db = { - "AFINN_96": "\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n", - "AFINN_111": "\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n", - "alias2pkg": "\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n", - "alias2related": "\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n", - "aliases": "\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n", - "allocUnsafe": "\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n", - "anova1": "\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n", - "ANSCOMBES_QUARTET": "\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n", - "any": "\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n", - "anyBy": "\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n", - "anyByAsync": "\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n", - "anyByRight": "\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n", - "anyByRightAsync": "\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n", - "APERY": "\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n", - "append": "\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n", - "ARCH": "\nARCH\n Operating system CPU architecture.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n", - "argumentFunction": "\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n", - "ARGV": "\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n", - "array": "\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n", - "array2buffer": "\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n", - "array2iterator": "\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n", - "array2iteratorRight": "\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n", - "ArrayBuffer": "\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n", - "arraybuffer2buffer": "\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n", - "arrayCtors": "\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n", - "arrayDataType": "\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n", - "arrayDataTypes": "\narrayDataTypes()\n Returns a list of array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n \n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n", - "arrayMinDataType": "\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n", - "arrayNextDataType": "\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n", - "arrayPromotionRules": "\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Array data type.\n\n dtype2: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n", - "arraySafeCasts": "\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySameKindCasts, ndarraySafeCasts\n", - "arraySameKindCasts": "\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n", - "arrayShape": "\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n", - "arrayStream": "\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n", - "arrayview2iterator": "\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n", - "arrayview2iteratorRight": "\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n", - "AsyncIteratorSymbol": "\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n", - "bartlettTest": "\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups })\n\n See Also\n --------\n vartest\n", - "base.abs": "\nbase.abs( x )\n Computes the absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2\n", - "base.abs2": "\nbase.abs2( x )\n Computes the squared absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs\n", - "base.absdiff": "\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n", - "base.absInt32": "\nbase.absInt32( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.absInt32( -1|0 )\n 1\n > v = base.absInt32( 2|0 )\n 2\n > v = base.absInt32( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n", - "base.acos": "\nbase.acos( x )\n Compute the arccosine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n", - "base.acosh": "\nbase.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n", - "base.acoth": "\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent (in radians).\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atanh\n", - "base.acovercos": "\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n", - "base.acoversin": "\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n", - "base.ahavercos": "\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n", - "base.ahaversin": "\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n", - "base.asin": "\nbase.asin( x )\n Computes the arcsine of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( PI/2.0 )\n ~1.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n", - "base.asinh": "\nbase.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n", - "base.atan": "\nbase.atan( x )\n Computes the arctangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n", - "base.atan2": "\nbase.atan2( y, x )\n Evaluates the arctangent of the quotient of two numbers.\n\n Parameters\n ----------\n y: number\n Numerator.\n\n x: number\n Denominator.\n\n Returns\n -------\n out: number\n Arctangent of `y/x` (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n", - "base.atanh": "\nbase.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n", - "base.avercos": "\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n", - "base.aversin": "\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n", - "base.bernoulli": "\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.0\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n", - "base.besselj0": "\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n", - "base.besselj1": "\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n", - "base.bessely0": "\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n", - "base.bessely1": "\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n", - "base.beta": "\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n", - "base.betainc": "\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n", - "base.betaincinv": "\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n", - "base.betaln": "\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n", - "base.binet": "\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n", - "base.binomcoef": "\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n", - "base.binomcoefln": "\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n", - "base.boxcox": "\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv", - "base.boxcox1p": "\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv", - "base.boxcox1pinv": "\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv", - "base.boxcoxinv": "\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv", - "base.cabs": "\nbase.cabs( re, im )\n Computes the absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( 5.0, 3.0 )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n", - "base.cabs2": "\nbase.cabs2( re, im )\n Computes the squared absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( 5.0, 3.0 )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n", - "base.cadd": "\nbase.cadd( [out,] re1, im1, re2, im2 )\n Adds two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cadd( 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n\n // Provide an output array:\n > var out = new Float32Array( 2 );\n > y = base.cadd( out, 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n", - "base.cbrt": "\nbase.cbrt( x )\n Computes the cube root.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n", - "base.cceil": "\nbase.cceil( [out,] re, im )\n Rounds a complex number toward positive infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceil( 5.5, 3.3 )\n [ 6.0, 4.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cceil( out, 5.5, 3.3 )\n [ 6.0, 4.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n", - "base.cceiln": "\nbase.cceiln( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward positive\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cceiln( out, 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n", - "base.ccis": "\nbase.ccis( [out,] re, im )\n Computes the cis function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.ccis( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > var y = base.ccis( 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.ccis( out, 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n", - "base.cdiv": "\nbase.cdiv( [out,] re1, im1, re2, im2 )\n Divides two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cdiv( -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.cdiv( out, -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cadd, base.cmul, base.csub\n", - "base.ceil": "\nbase.ceil( x )\n Rounds a numeric value toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n", - "base.ceil2": "\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n", - "base.ceil10": "\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n", - "base.ceilb": "\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n", - "base.ceiln": "\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n", - "base.ceilsd": "\nbase.ceilsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1 )\n 4.0\n > y = base.ceilsd( 12368.0, 2 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n", - "base.cexp": "\nbase.cexp( [out,] re, im )\n Computes the exponential function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cexp( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > y = base.cexp( 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.cexp( out, 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n", - "base.cflipsign": "\nbase.cflipsign( [out,] re, im, y )\n Returns a complex number with the same magnitude as `z` and the sign of\n `y*z`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.cflipsign( -4.2, 5.5, -9 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cflipsign( out, -4.2, 5.5, 8 )\n [ -4.2, 5.5 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cneg, base.csignum\n", - "base.cfloor": "\nbase.cfloor( [out,] re, im )\n Rounds a complex number toward negative infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cfloor( 5.5, 3.3 )\n [ 5.0, 3.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cfloor( out, 5.5, 3.3 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n", - "base.cfloorn": "\nbase.cfloorn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward negative\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cfloorn( 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cfloorn( out, 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n", - "base.cinv": "\nbase.cinv( [out,] re, im )\n Computes the inverse of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cinv( 2.0, 4.0 )\n [ 0.1, -0.2 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.cinv( out, 2.0, 4.0 )\n [ 0.1, -0.2 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cdiv\n", - "base.clamp": "\nbase.clamp( v, min, max )\n Restricts a value to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.wrap\n", - "base.cmul": "\nbase.cmul( [out,] re1, im1, re2, im2 )\n Multiplies two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.cmul( 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n\n // Provide an output array:\n > var out = new Float64Array( 2 );\n > var v = base.cmul( out, 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n", - "base.cneg": "\nbase.cneg( [out,] re, im )\n Negates a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Negated components.\n\n Examples\n --------\n > var out = base.cneg( -4.2, 5.5 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cneg( out, -4.2, 5.5 )\n [ 4.2, -5.5 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs\n", - "base.continuedFraction": "\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n", - "base.copysign": "\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n", - "base.cos": "\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n", - "base.cosh": "\nbase.cosh( x )\n Computes the hyperbolic cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n", - "base.cosm1": "\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n", - "base.cospi": "\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n", - "base.covercos": "\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n", - "base.coversin": "\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n", - "base.cphase": "\nbase.cphase( re, im )\n Computes the argument of a complex number in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( 5.0, 3.0 )\n ~0.5404\n\n See Also\n --------\n base.cabs\n", - "base.cpolar": "\nbase.cpolar( [out,] re, im )\n Returns the absolute value and phase of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cpolar( out, 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase\n", - "base.cround": "\nbase.cround( [out,] re, im )\n Rounds a complex number to the nearest integer.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cround( 5.5, 3.3 )\n [ 6.0, 3.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cround( out, 5.5, 3.3 )\n [ 6.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n", - "base.croundn": "\nbase.croundn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.croundn( 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.croundn( out, 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n", - "base.csignum": "\nbase.csignum( [out,] re, im )\n Evaluates the signum function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.csignum( -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.csignum( out, -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.signum\n", - "base.csub": "\nbase.csub( [out,] re1, im1, re2, im2 )\n Subtracts two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.csub( 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.csub( out, 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n", - "base.dasum": "\nbase.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > sum = base.dasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > sum = base.dasum( N, x1, stride )\n 12.0\n\n\nbase.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n\nbase.dasum.wasm( [options] )\n Returns a memory managed function to compute the sum of absolute values.\n\n For an externally defined `Float64Array`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.dasum.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var bytes = wasm.malloc( N * 8 );\n\n // Create a Float64Array view:\n > var view = new Float64Array( bytes.buffer, bytes.byteOffset, N );\n\n // Copy data to the heap:\n > view.set( [ 1.0, -2.0, 3.0, -4.0, 5.0 ] );\n\n // Compute the sum of absolute values (passing in the heap buffer):\n > var s = wasm( N, bytes, 1 )\n 15.0\n\n // Free the memory:\n > wasm.free( bytes );\n\n See Also\n --------\n base.daxpy, base.dcopy\n", - "base.daxpy": "\nbase.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.daxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.daxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.daxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.wasm( [options] )\n Returns a memory managed function to multiply `x` by a constant `alpha` and\n add the result to `y`.\n\n For externally defined `Float64Arrays`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.daxpy.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var xbytes = wasm.malloc( N * 8 );\n > var ybytes = wasm.malloc( N * 8 );\n\n // Create Float64Array views:\n > var x = new Float64Array( xbytes.buffer, xbytes.byteOffset, N );\n > var y = new Float64Array( ybytes.buffer, ybytes.byteOffset, N );\n\n // Copy data to the heap:\n > x.set( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > y.set( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n\n // Multiply and add alpha:\n > var alpha = 5.0;\n > wasm( x.length, alpha, xbytes, 1, ybytes, 1 );\n > y\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Free the memory:\n > wasm.free( xbytes );\n > wasm.free( ybytes );\n\n See Also\n --------\n base.dasum, base.dcopy\n", - "base.dcopy": "\nbase.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.dcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.dcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.dcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.dasum, base.daxpy\n", - "base.deg2rad": "\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n", - "base.digamma": "\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.trigamma, base.gamma\n", - "base.diracDelta": "\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n", - "base.dists.arcsine.Arcsine": "\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n", - "base.dists.arcsine.cdf": "\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n", - "base.dists.arcsine.entropy": "\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n", - "base.dists.arcsine.kurtosis": "\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n", - "base.dists.arcsine.logcdf": "\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n", - "base.dists.arcsine.logpdf": "\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n", - "base.dists.arcsine.mean": "\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n", - "base.dists.arcsine.median": "\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n", - "base.dists.arcsine.mode": "\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n", - "base.dists.arcsine.pdf": "\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n", - "base.dists.arcsine.quantile": "\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n", - "base.dists.arcsine.skewness": "\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n", - "base.dists.arcsine.stdev": "\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n", - "base.dists.arcsine.variance": "\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n", - "base.dists.bernoulli.Bernoulli": "\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n", - "base.dists.bernoulli.cdf": "\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n", - "base.dists.bernoulli.entropy": "\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n", - "base.dists.bernoulli.kurtosis": "\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n", - "base.dists.bernoulli.mean": "\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n", - "base.dists.bernoulli.median": "\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n", - "base.dists.bernoulli.mgf": "\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n", - "base.dists.bernoulli.mode": "\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n", - "base.dists.bernoulli.pmf": "\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n", - "base.dists.bernoulli.quantile": "\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n", - "base.dists.bernoulli.skewness": "\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n", - "base.dists.bernoulli.stdev": "\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n", - "base.dists.bernoulli.variance": "\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n", - "base.dists.beta.Beta": "\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n", - "base.dists.beta.cdf": "\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n", - "base.dists.beta.entropy": "\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n", - "base.dists.beta.kurtosis": "\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n", - "base.dists.beta.logcdf": "\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n", - "base.dists.beta.logpdf": "\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n", - "base.dists.beta.mean": "\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n", - "base.dists.beta.median": "\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n", - "base.dists.beta.mgf": "\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n", - "base.dists.beta.mode": "\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n", - "base.dists.beta.pdf": "\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n", - "base.dists.beta.quantile": "\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n", - "base.dists.beta.skewness": "\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n", - "base.dists.beta.stdev": "\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n", - "base.dists.beta.variance": "\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n", - "base.dists.betaprime.BetaPrime": "\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n", - "base.dists.betaprime.cdf": "\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n", - "base.dists.betaprime.kurtosis": "\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n", - "base.dists.betaprime.logcdf": "\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n", - "base.dists.betaprime.logpdf": "\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n", - "base.dists.betaprime.mean": "\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n", - "base.dists.betaprime.mode": "\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n", - "base.dists.betaprime.pdf": "\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n", - "base.dists.betaprime.quantile": "\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n", - "base.dists.betaprime.skewness": "\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n", - "base.dists.betaprime.stdev": "\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n", - "base.dists.betaprime.variance": "\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n", - "base.dists.binomial.Binomial": "\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n", - "base.dists.binomial.cdf": "\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n", - "base.dists.binomial.entropy": "\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n", - "base.dists.binomial.kurtosis": "\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n", - "base.dists.binomial.logpmf": "\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n", - "base.dists.binomial.mean": "\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n", - "base.dists.binomial.median": "\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n", - "base.dists.binomial.mgf": "\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n", - "base.dists.binomial.mode": "\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n", - "base.dists.binomial.pmf": "\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n", - "base.dists.binomial.quantile": "\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n", - "base.dists.binomial.skewness": "\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n", - "base.dists.binomial.stdev": "\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n", - "base.dists.binomial.variance": "\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n", - "base.dists.cauchy.Cauchy": "\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n", - "base.dists.cauchy.cdf": "\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n", - "base.dists.cauchy.entropy": "\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n", - "base.dists.cauchy.logcdf": "\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n", - "base.dists.cauchy.logpdf": "\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n", - "base.dists.cauchy.median": "\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n", - "base.dists.cauchy.mode": "\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n", - "base.dists.cauchy.pdf": "\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n", - "base.dists.cauchy.quantile": "\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n", - "base.dists.chi.cdf": "\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n", - "base.dists.chi.Chi": "\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n", - "base.dists.chi.entropy": "\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n", - "base.dists.chi.kurtosis": "\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n", - "base.dists.chi.logpdf": "\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n", - "base.dists.chi.mean": "\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n", - "base.dists.chi.mode": "\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n", - "base.dists.chi.pdf": "\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n", - "base.dists.chi.quantile": "\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n", - "base.dists.chi.skewness": "\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n", - "base.dists.chi.stdev": "\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n", - "base.dists.chi.variance": "\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n", - "base.dists.chisquare.cdf": "\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n", - "base.dists.chisquare.ChiSquare": "\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n", - "base.dists.chisquare.entropy": "\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n", - "base.dists.chisquare.kurtosis": "\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n", - "base.dists.chisquare.logpdf": "\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n", - "base.dists.chisquare.mean": "\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n", - "base.dists.chisquare.mode": "\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n", - "base.dists.chisquare.pdf": "\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n", - "base.dists.chisquare.quantile": "\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n", - "base.dists.chisquare.skewness": "\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n", - "base.dists.chisquare.stdev": "\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n", - "base.dists.chisquare.variance": "\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n", - "base.dists.cosine.cdf": "\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n", - "base.dists.cosine.Cosine": "\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n", - "base.dists.cosine.kurtosis": "\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n", - "base.dists.cosine.logcdf": "\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n", - "base.dists.cosine.logpdf": "\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n", - "base.dists.cosine.mean": "\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n", - "base.dists.cosine.median": "\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n", - "base.dists.cosine.mgf": "\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n", - "base.dists.cosine.mode": "\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n", - "base.dists.cosine.pdf": "\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n", - "base.dists.cosine.quantile": "\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n", - "base.dists.cosine.skewness": "\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n", - "base.dists.cosine.stdev": "\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n", - "base.dists.cosine.variance": "\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n", - "base.dists.degenerate.cdf": "\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n", - "base.dists.degenerate.Degenerate": "\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n", - "base.dists.degenerate.entropy": "\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n", - "base.dists.degenerate.logcdf": "\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n", - "base.dists.degenerate.logpdf": "\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n", - "base.dists.degenerate.logpmf": "\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n", - "base.dists.degenerate.mean": "\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n", - "base.dists.degenerate.median": "\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n", - "base.dists.degenerate.mgf": "\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n", - "base.dists.degenerate.mode": "\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n", - "base.dists.degenerate.pdf": "\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n", - "base.dists.degenerate.pmf": "\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n", - "base.dists.degenerate.quantile": "\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n", - "base.dists.degenerate.stdev": "\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n", - "base.dists.degenerate.variance": "\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n", - "base.dists.discreteUniform.cdf": "\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n", - "base.dists.discreteUniform.DiscreteUniform": "\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n", - "base.dists.discreteUniform.kurtosis": "\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n", - "base.dists.discreteUniform.logcdf": "\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n", - "base.dists.discreteUniform.logpmf": "\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n", - "base.dists.discreteUniform.mean": "\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n", - "base.dists.discreteUniform.median": "\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n", - "base.dists.discreteUniform.mgf": "\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n", - "base.dists.discreteUniform.pmf": "\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n", - "base.dists.discreteUniform.quantile": "\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n", - "base.dists.discreteUniform.skewness": "\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n", - "base.dists.discreteUniform.stdev": "\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n", - "base.dists.discreteUniform.variance": "\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n", - "base.dists.erlang.cdf": "\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n", - "base.dists.erlang.entropy": "\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n", - "base.dists.erlang.Erlang": "\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n", - "base.dists.erlang.kurtosis": "\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n", - "base.dists.erlang.logpdf": "\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n", - "base.dists.erlang.mean": "\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n", - "base.dists.erlang.mgf": "\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n", - "base.dists.erlang.mode": "\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n", - "base.dists.erlang.pdf": "\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n", - "base.dists.erlang.quantile": "\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n", - "base.dists.erlang.skewness": "\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n", - "base.dists.erlang.stdev": "\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n", - "base.dists.erlang.variance": "\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n", - "base.dists.exponential.cdf": "\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n", - "base.dists.exponential.entropy": "\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n", - "base.dists.exponential.Exponential": "\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n", - "base.dists.exponential.kurtosis": "\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n", - "base.dists.exponential.logcdf": "\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n", - "base.dists.exponential.logpdf": "\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n", - "base.dists.exponential.mean": "\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n", - "base.dists.exponential.median": "\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n", - "base.dists.exponential.mode": "\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n", - "base.dists.exponential.pdf": "\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n", - "base.dists.exponential.quantile": "\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n", - "base.dists.exponential.skewness": "\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n", - "base.dists.exponential.stdev": "\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n", - "base.dists.exponential.variance": "\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n", - "base.dists.f.cdf": "\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n", - "base.dists.f.entropy": "\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of a F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n", - "base.dists.f.F": "\nbase.dists.f.F( [d1, d2] )\n Returns a F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n", - "base.dists.f.kurtosis": "\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of a F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n", - "base.dists.f.mean": "\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of a F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n", - "base.dists.f.mode": "\nbase.dists.f.mode( d1, d2 )\n Returns the mode of a F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n", - "base.dists.f.pdf": "\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for a F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n", - "base.dists.f.quantile": "\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for a F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n", - "base.dists.f.skewness": "\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of a F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n", - "base.dists.f.stdev": "\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of a F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n", - "base.dists.f.variance": "\nbase.dists.f.variance( d1, d2 )\n Returns the variance of a F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n", - "base.dists.frechet.cdf": "\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n", - "base.dists.frechet.entropy": "\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n", - "base.dists.frechet.Frechet": "\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n", - "base.dists.frechet.kurtosis": "\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n", - "base.dists.frechet.logcdf": "\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n", - "base.dists.frechet.logpdf": "\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n", - "base.dists.frechet.mean": "\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n", - "base.dists.frechet.median": "\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n", - "base.dists.frechet.mode": "\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n", - "base.dists.frechet.pdf": "\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n", - "base.dists.frechet.quantile": "\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n", - "base.dists.frechet.skewness": "\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n", - "base.dists.frechet.stdev": "\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n", - "base.dists.frechet.variance": "\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n", - "base.dists.gamma.cdf": "\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n", - "base.dists.gamma.entropy": "\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n", - "base.dists.gamma.Gamma": "\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n", - "base.dists.gamma.kurtosis": "\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n", - "base.dists.gamma.logpdf": "\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n", - "base.dists.gamma.mean": "\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n", - "base.dists.gamma.mgf": "\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n", - "base.dists.gamma.mode": "\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n", - "base.dists.gamma.pdf": "\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n", - "base.dists.gamma.quantile": "\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n", - "base.dists.gamma.skewness": "\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n", - "base.dists.gamma.stdev": "\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n", - "base.dists.gamma.variance": "\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n", - "base.dists.geometric.cdf": "\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n", - "base.dists.geometric.entropy": "\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n", - "base.dists.geometric.Geometric": "\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n", - "base.dists.geometric.kurtosis": "\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n", - "base.dists.geometric.logcdf": "\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n", - "base.dists.geometric.logpmf": "\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n", - "base.dists.geometric.mean": "\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n", - "base.dists.geometric.median": "\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n", - "base.dists.geometric.mgf": "\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n", - "base.dists.geometric.mode": "\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n", - "base.dists.geometric.pmf": "\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n", - "base.dists.geometric.quantile": "\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n", - "base.dists.geometric.skewness": "\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n", - "base.dists.geometric.stdev": "\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n", - "base.dists.geometric.variance": "\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n", - "base.dists.gumbel.cdf": "\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n", - "base.dists.gumbel.entropy": "\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n", - "base.dists.gumbel.Gumbel": "\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n", - "base.dists.gumbel.kurtosis": "\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n", - "base.dists.gumbel.logcdf": "\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n", - "base.dists.gumbel.logpdf": "\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n", - "base.dists.gumbel.mean": "\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n", - "base.dists.gumbel.median": "\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n", - "base.dists.gumbel.mgf": "\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n", - "base.dists.gumbel.mode": "\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n", - "base.dists.gumbel.pdf": "\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n", - "base.dists.gumbel.quantile": "\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n", - "base.dists.gumbel.skewness": "\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n", - "base.dists.gumbel.stdev": "\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n", - "base.dists.gumbel.variance": "\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n", - "base.dists.hypergeometric.cdf": "\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n", - "base.dists.hypergeometric.Hypergeometric": "\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n", - "base.dists.hypergeometric.kurtosis": "\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n", - "base.dists.hypergeometric.logpmf": "\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n", - "base.dists.hypergeometric.mean": "\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n", - "base.dists.hypergeometric.mode": "\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n", - "base.dists.hypergeometric.pmf": "\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n", - "base.dists.hypergeometric.quantile": "\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n", - "base.dists.hypergeometric.skewness": "\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n", - "base.dists.hypergeometric.stdev": "\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n", - "base.dists.hypergeometric.variance": "\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n", - "base.dists.invgamma.cdf": "\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n", - "base.dists.invgamma.entropy": "\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n", - "base.dists.invgamma.InvGamma": "\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n", - "base.dists.invgamma.kurtosis": "\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n", - "base.dists.invgamma.logpdf": "\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n", - "base.dists.invgamma.mean": "\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n", - "base.dists.invgamma.mode": "\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n", - "base.dists.invgamma.pdf": "\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n", - "base.dists.invgamma.quantile": "\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n", - "base.dists.invgamma.skewness": "\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n", - "base.dists.invgamma.stdev": "\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n", - "base.dists.invgamma.variance": "\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n", - "base.dists.kumaraswamy.cdf": "\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n", - "base.dists.kumaraswamy.Kumaraswamy": "\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n", - "base.dists.kumaraswamy.kurtosis": "\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n", - "base.dists.kumaraswamy.logcdf": "\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n", - "base.dists.kumaraswamy.logpdf": "\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n", - "base.dists.kumaraswamy.mean": "\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n", - "base.dists.kumaraswamy.median": "\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n", - "base.dists.kumaraswamy.mode": "\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n", - "base.dists.kumaraswamy.pdf": "\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n", - "base.dists.kumaraswamy.quantile": "\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n", - "base.dists.kumaraswamy.skewness": "\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n", - "base.dists.kumaraswamy.stdev": "\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n", - "base.dists.kumaraswamy.variance": "\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n", - "base.dists.laplace.cdf": "\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n", - "base.dists.laplace.entropy": "\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n", - "base.dists.laplace.kurtosis": "\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n", - "base.dists.laplace.Laplace": "\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n", - "base.dists.laplace.logcdf": "\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n", - "base.dists.laplace.logpdf": "\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n", - "base.dists.laplace.mean": "\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n", - "base.dists.laplace.median": "\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n", - "base.dists.laplace.mgf": "\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n", - "base.dists.laplace.mode": "\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n", - "base.dists.laplace.pdf": "\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n", - "base.dists.laplace.quantile": "\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n", - "base.dists.laplace.skewness": "\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n", - "base.dists.laplace.stdev": "\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n", - "base.dists.laplace.variance": "\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n", - "base.dists.levy.cdf": "\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n", - "base.dists.levy.entropy": "\nbase.dists.levy.entropy( μ, c )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n", - "base.dists.levy.Levy": "\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n", - "base.dists.levy.logcdf": "\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n", - "base.dists.levy.logpdf": "\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n", - "base.dists.levy.mean": "\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n", - "base.dists.levy.median": "\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n", - "base.dists.levy.mode": "\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n", - "base.dists.levy.pdf": "\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n", - "base.dists.levy.quantile": "\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n", - "base.dists.levy.stdev": "\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n", - "base.dists.levy.variance": "\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n", - "base.dists.logistic.cdf": "\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n", - "base.dists.logistic.entropy": "\nbase.dists.logistic.entropy( μ, s )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n", - "base.dists.logistic.kurtosis": "\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n", - "base.dists.logistic.logcdf": "\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n", - "base.dists.logistic.Logistic": "\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n", - "base.dists.logistic.logpdf": "\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n", - "base.dists.logistic.mean": "\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n", - "base.dists.logistic.median": "\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n", - "base.dists.logistic.mgf": "\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n", - "base.dists.logistic.mode": "\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n", - "base.dists.logistic.pdf": "\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n", - "base.dists.logistic.quantile": "\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n", - "base.dists.logistic.skewness": "\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n", - "base.dists.logistic.stdev": "\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n", - "base.dists.logistic.variance": "\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n", - "base.dists.lognormal.cdf": "\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n", - "base.dists.lognormal.entropy": "\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n", - "base.dists.lognormal.kurtosis": "\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n", - "base.dists.lognormal.LogNormal": "\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n", - "base.dists.lognormal.logpdf": "\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n", - "base.dists.lognormal.mean": "\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n", - "base.dists.lognormal.median": "\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n", - "base.dists.lognormal.mode": "\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n", - "base.dists.lognormal.pdf": "\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n", - "base.dists.lognormal.quantile": "\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n", - "base.dists.lognormal.skewness": "\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n", - "base.dists.lognormal.stdev": "\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n", - "base.dists.lognormal.variance": "\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n", - "base.dists.negativeBinomial.cdf": "\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n", - "base.dists.negativeBinomial.kurtosis": "\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n", - "base.dists.negativeBinomial.logpmf": "\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n", - "base.dists.negativeBinomial.mean": "\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n", - "base.dists.negativeBinomial.mgf": "\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n", - "base.dists.negativeBinomial.mode": "\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n", - "base.dists.negativeBinomial.NegativeBinomial": "\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n", - "base.dists.negativeBinomial.pmf": "\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n", - "base.dists.negativeBinomial.quantile": "\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n", - "base.dists.negativeBinomial.skewness": "\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n", - "base.dists.negativeBinomial.stdev": "\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n", - "base.dists.negativeBinomial.variance": "\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n", - "base.dists.normal.cdf": "\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n", - "base.dists.normal.entropy": "\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n", - "base.dists.normal.kurtosis": "\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n", - "base.dists.normal.logpdf": "\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n", - "base.dists.normal.mean": "\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n", - "base.dists.normal.median": "\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n", - "base.dists.normal.mgf": "\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n", - "base.dists.normal.mode": "\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n", - "base.dists.normal.Normal": "\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n", - "base.dists.normal.pdf": "\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n", - "base.dists.normal.quantile": "\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n", - "base.dists.normal.skewness": "\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n", - "base.dists.normal.stdev": "\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n", - "base.dists.normal.variance": "\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n", - "base.dists.pareto1.cdf": "\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n", - "base.dists.pareto1.entropy": "\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n", - "base.dists.pareto1.kurtosis": "\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n", - "base.dists.pareto1.logcdf": "\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n", - "base.dists.pareto1.logpdf": "\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n", - "base.dists.pareto1.mean": "\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n", - "base.dists.pareto1.median": "\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n", - "base.dists.pareto1.mode": "\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n", - "base.dists.pareto1.Pareto1": "\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n", - "base.dists.pareto1.pdf": "\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n", - "base.dists.pareto1.quantile": "\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n", - "base.dists.pareto1.skewness": "\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n", - "base.dists.pareto1.variance": "\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n", - "base.dists.poisson.cdf": "\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n", - "base.dists.poisson.entropy": "\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n", - "base.dists.poisson.kurtosis": "\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n", - "base.dists.poisson.logpmf": "\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n", - "base.dists.poisson.mean": "\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n", - "base.dists.poisson.median": "\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n", - "base.dists.poisson.mode": "\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n", - "base.dists.poisson.pmf": "\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n", - "base.dists.poisson.Poisson": "\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n", - "base.dists.poisson.quantile": "\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n", - "base.dists.poisson.skewness": "\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n", - "base.dists.poisson.stdev": "\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n", - "base.dists.poisson.variance": "\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n", - "base.dists.rayleigh.cdf": "\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n", - "base.dists.rayleigh.entropy": "\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n", - "base.dists.rayleigh.kurtosis": "\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n", - "base.dists.rayleigh.logcdf": "\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n", - "base.dists.rayleigh.logpdf": "\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n", - "base.dists.rayleigh.mean": "\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n", - "base.dists.rayleigh.median": "\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n", - "base.dists.rayleigh.mgf": "\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n", - "base.dists.rayleigh.mode": "\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n", - "base.dists.rayleigh.pdf": "\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n", - "base.dists.rayleigh.quantile": "\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n", - "base.dists.rayleigh.Rayleigh": "\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n", - "base.dists.rayleigh.skewness": "\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n", - "base.dists.rayleigh.stdev": "\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n", - "base.dists.rayleigh.variance": "\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n", - "base.dists.t.cdf": "\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n", - "base.dists.t.entropy": "\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n", - "base.dists.t.kurtosis": "\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n", - "base.dists.t.mean": "\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n", - "base.dists.t.median": "\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n", - "base.dists.t.mode": "\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n", - "base.dists.t.pdf": "\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n", - "base.dists.t.quantile": "\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n", - "base.dists.t.skewness": "\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n", - "base.dists.t.stdev": "\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n", - "base.dists.t.T": "\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n", - "base.dists.t.variance": "\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n", - "base.dists.triangular.cdf": "\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n", - "base.dists.triangular.entropy": "\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n", - "base.dists.triangular.kurtosis": "\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n", - "base.dists.triangular.logcdf": "\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n", - "base.dists.triangular.logpdf": "\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n", - "base.dists.triangular.mean": "\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n", - "base.dists.triangular.median": "\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n", - "base.dists.triangular.mgf": "\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n", - "base.dists.triangular.mode": "\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n", - "base.dists.triangular.pdf": "\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n", - "base.dists.triangular.quantile": "\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n", - "base.dists.triangular.skewness": "\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n", - "base.dists.triangular.stdev": "\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n", - "base.dists.triangular.Triangular": "\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n", - "base.dists.triangular.variance": "\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n", - "base.dists.uniform.cdf": "\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n", - "base.dists.uniform.entropy": "\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n", - "base.dists.uniform.kurtosis": "\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n", - "base.dists.uniform.logcdf": "\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n", - "base.dists.uniform.logpdf": "\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n", - "base.dists.uniform.mean": "\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n", - "base.dists.uniform.median": "\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n", - "base.dists.uniform.mgf": "\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n", - "base.dists.uniform.pdf": "\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n", - "base.dists.uniform.quantile": "\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n", - "base.dists.uniform.skewness": "\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n", - "base.dists.uniform.stdev": "\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n", - "base.dists.uniform.Uniform": "\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n", - "base.dists.uniform.variance": "\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n", - "base.dists.weibull.cdf": "\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n", - "base.dists.weibull.entropy": "\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n", - "base.dists.weibull.kurtosis": "\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n", - "base.dists.weibull.logcdf": "\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n", - "base.dists.weibull.logpdf": "\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n", - "base.dists.weibull.mean": "\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n", - "base.dists.weibull.median": "\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n", - "base.dists.weibull.mgf": "\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n", - "base.dists.weibull.mode": "\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n", - "base.dists.weibull.pdf": "\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n", - "base.dists.weibull.quantile": "\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n", - "base.dists.weibull.skewness": "\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n", - "base.dists.weibull.stdev": "\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n", - "base.dists.weibull.variance": "\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n", - "base.dists.weibull.Weibull": "\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n", - "base.ellipe": "\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipk\n", - "base.ellipk": "\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe\n", - "base.epsdiff": "\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n", - "base.erf": "\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n", - "base.erfc": "\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv\n", - "base.erfcinv": "\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv\n", - "base.erfinv": "\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n", - "base.eta": "\nbase.eta( s )\n Evaluates the Dirichlet eta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n", - "base.evalpoly": "\nbase.evalpoly( c, x )\n Evaluates a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n", - "base.evalrational": "\nbase.evalrational( P, Q, x )\n Evaluates a rational function.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n", - "base.exp": "\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n", - "base.exp2": "\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10\n", - "base.exp10": "\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2\n", - "base.expit": "\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit", - "base.expm1": "\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n", - "base.expm1rel": "\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n See Also\n --------\n base.exp, base.expm1\n", - "base.exponent": "\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n", - "base.exponentf": "\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n", - "base.factorial": "\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n", - "base.factorialln": "\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n", - "base.fallingFactorial": "\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n", - "base.fibonacci": "\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n", - "base.fibonacciIndex": "\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n", - "base.fibpoly": "\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n", - "base.flipsign": "\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`, else behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.14, 10.0 )\n -3.14\n > z = base.flipsign( -3.14, -1.0 )\n 3.14\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.14, -0.0 )\n 3.14\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n", - "base.float32ToInt32": "\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n -1\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32", - "base.float32ToUint32": "\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 1\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32", - "base.float64ToFloat32": "\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n", - "base.float64ToInt32": "\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32", - "base.float64ToUint32": "\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32", - "base.floor": "\nbase.floor( x )\n Rounds a numeric value toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n", - "base.floor2": "\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n", - "base.floor10": "\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n", - "base.floorb": "\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n", - "base.floorn": "\nbase.floorn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward negative\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n", - "base.floorsd": "\nbase.floorsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5 )\n 3.1415\n > y = base.floorsd( 3.14159, 1 )\n 3.0\n > y = base.floorsd( 12368.0, 2 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n", - "base.fresnel": "\nbase.fresnel( [out,] x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n > var out = new Float64Array( 2 );\n > var v = base.fresnel( out, 0.0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels\n", - "base.fresnelc": "\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n", - "base.fresnels": "\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n", - "base.frexp": "\nbase.frexp( [out,] x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var y = base.frexp( out, 4.0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n", - "base.fromBinaryString": "\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n", - "base.fromBinaryStringf": "\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n", - "base.fromBinaryStringUint8": "\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n", - "base.fromBinaryStringUint16": "\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n", - "base.fromBinaryStringUint32": "\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n", - "base.fromWordf": "\nbase.fromWordf( x )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n", - "base.fromWords": "\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n", - "base.gamma": "\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n", - "base.gamma1pm1": "\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n", - "base.gammaDeltaRatio": "\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n", - "base.gammainc": "\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n", - "base.gammaincinv": "\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n", - "base.gammaLanczosSum": "\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n", - "base.gammaLanczosSumExpGScaled": "\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n", - "base.gammaln": "\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n", - "base.gasum": "\nbase.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > sum = base.gasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > sum = base.gasum( N, x1, stride )\n 12.0\n\n\nbase.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > sum = base.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.dasum, base.sasum\n", - "base.gaxpy": "\nbase.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > base.gaxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.gaxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = base.floor( x.length / 2 );\n > base.gaxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.daxpy, base.saxpy\n", - "base.gcd": "\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n", - "base.gcopy": "\nbase.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = base.floor( x.length / 2 );\n > base.gcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.gcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = base.floor( x.length / 2 );\n > base.gcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.dcopy\n", - "base.getHighWord": "\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n", - "base.getLowWord": "\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n", - "base.hacovercos": "\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n", - "base.hacoversin": "\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n", - "base.havercos": "\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n", - "base.haversin": "\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n", - "base.heaviside": "\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n", - "base.hermitepoly": "\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n", - "base.hypot": "\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n", - "base.imul": "\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw, base.uimul\n", - "base.imuldw": "\nbase.imuldw( [out,] a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n See Also\n --------\n base.imul, base.uimuldw\n", - "base.int32ToUint32": "\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n", - "base.inv": "\nbase.inv( x )\n Computes the multiplicative inverse of `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n", - "base.isEven": "\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n", - "base.isEvenInt32": "\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n", - "base.isFinite": "\nbase.isFinite( x )\n Tests if a numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n", - "base.isInfinite": "\nbase.isInfinite( x )\n Tests if a numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n", - "base.isInteger": "\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n", - "base.isnan": "\nbase.isnan( x )\n Tests if a numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n", - "base.isNegativeInteger": "\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n", - "base.isNegativeZero": "\nbase.isNegativeZero( x )\n Tests if a numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n", - "base.isNonNegativeInteger": "\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n", - "base.isNonPositiveInteger": "\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n", - "base.isOdd": "\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n", - "base.isOddInt32": "\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n", - "base.isPositiveInteger": "\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n", - "base.isPositiveZero": "\nbase.isPositiveZero( x )\n Tests if a numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n", - "base.isPow2Uint32": "\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n", - "base.isProbability": "\nbase.isProbability( x )\n Tests if a numeric value is a probability.\n\n A probability is defined as a numeric value on the closed interval `[0,1]`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n", - "base.isSafeInteger": "\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n", - "base.kernelBetainc": "\nbase.kernelBetainc( [out,] x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.32, 1.6 ]\n\n > out = new Array( 2 );\n > var v = base.kernelBetainc( out, 0.2, 1.0, 2.0, true, true )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n", - "base.kernelBetaincinv": "\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n", - "base.kernelCos": "\nbase.kernelCos( x, y )\n Computes the cosine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n", - "base.kernelSin": "\nbase.kernelSin( x, y )\n Computes the sine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n", - "base.kernelTan": "\nbase.kernelTan( x, y, k )\n Computes the tangent of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n", - "base.kroneckerDelta": "\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n", - "base.lcm": "\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n", - "base.ldexp": "\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n", - "base.ln": "\nbase.ln( x )\n Evaluates the natural logarithm.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n", - "base.log": "\nbase.log( x, b )\n Computes the base `b` logarithm of `x`.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n", - "base.log1mexp": "\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp", - "base.log1p": "\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n", - "base.log1pexp": "\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p", - "base.log2": "\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n", - "base.log10": "\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n", - "base.logaddexp": "\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n", - "base.logit": "\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n", - "base.lucas": "\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n", - "base.lucaspoly": "\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n", - "base.max": "\nbase.max( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n", - "base.maxabs": "\nbase.maxabs( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n", - "base.min": "\nbase.min( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs\n", - "base.minabs": "\nbase.minabs( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n", - "base.minmax": "\nbase.minmax( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmax( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmax( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs\n", - "base.minmaxabs": "\nbase.minmaxabs( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabs( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmaxabs( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n", - "base.modf": "\nbase.modf( [out,] x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n parts: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new Float64Array( 2 );\n > parts = base.modf( out, 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n\n", - "base.ndarray": "\nbase.ndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarray( 'float64', 3 )\n \n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n See Also\n --------\n array, ndarray\n", - "base.ndarrayMemoized": "\nbase.ndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarrayMemoized( 'float64', 3 )\n \n > var f = base.ndarrayMemoized( 'float64', 3 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n See Also\n --------\n array, base.ndarray, ndarray, ndarrayMemoized\n", - "base.negafibonacci": "\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n", - "base.negalucas": "\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n", - "base.nonfibonacci": "\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n", - "base.normalize": "\nbase.normalize( [out,] x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.normalize( out, 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n", - "base.normalizef": "\nbase.normalizef( [out,] x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new Float32Array( 2 );\n > var v = base.normalizef( out, base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize\n", - "base.normhermitepoly": "\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n", - "base.pdiff": "\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n", - "base.polygamma": "\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n", - "base.pow": "\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n", - "base.powm1": "\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n", - "base.rad2deg": "\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n", - "base.ramp": "\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n", - "base.random.arcsine": "\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.beta\n", - "base.random.bernoulli": "\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.binomial\n", - "base.random.beta": "\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.betaprime": "\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.binomial": "\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.boxMuller": "\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.cauchy": "\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.chi": "\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.chisquare": "\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.cosine": "\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.discreteUniform": "\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.erlang": "\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.exponential": "\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.f": "\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.frechet": "\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.gamma": "\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.geometric": "\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.gumbel": "\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.hypergeometric": "\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.improvedZiggurat": "\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.invgamma": "\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.kumaraswamy": "\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.laplace": "\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.levy": "\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.logistic": "\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.lognormal": "\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.minstd": "\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstdShuffle, base.random.mt19937, base.random.randi\n", - "base.random.minstdShuffle": "\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstd, base.random.mt19937, base.random.randi\n", - "base.random.mt19937": "\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[1, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 1\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstd, base.random.randi\n", - "base.random.negativeBinomial": "\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.normal": "\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.pareto1": "\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.poisson": "\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.randi": "\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n", - "base.random.randn": "\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.improvedZiggurat, base.random.randu\n", - "base.random.randu": "\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.discreteUniform, base.random.randn\n", - "base.random.rayleigh": "\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.t": "\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function\n returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.triangular": "\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.random.uniform": "\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.discreteUniform, base.random.randu\n", - "base.random.weibull": "\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n", - "base.reldiff": "\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n", - "base.rempio2": "\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = new Array( 2 );\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n", - "base.risingFactorial": "\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n", - "base.rotl32": "\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n", - "base.rotr32": "\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n", - "base.round": "\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n", - "base.round2": "\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n", - "base.round10": "\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n", - "base.roundb": "\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n", - "base.roundn": "\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n", - "base.roundsd": "\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n", - "base.rsqrt": "\nbase.rsqrt( x )\n Computes the reciprocal square root.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n", - "base.sasum": "\nbase.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > sum = base.sasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > sum = base.sasum( N, x1, stride )\n 12.0\n\n\nbase.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.dasum\n", - "base.saxpy": "\nbase.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > base.saxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.saxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.saxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.daxpy\n", - "base.scopy": "\nbase.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.scopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.scopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.scopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.dcopy\n", - "base.setHighWord": "\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n", - "base.setLowWord": "\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n", - "base.sici": "\nbase.sici( [out,] x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new Float64Array( 2 );\n > y = base.sici( out, 3.0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n\n", - "base.signbit": "\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n", - "base.signbitf": "\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n", - "base.significandf": "\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n", - "base.signum": "\nbase.signum( x )\n Evaluates the signum function.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n", - "base.sin": "\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n", - "base.sinc": "\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n", - "base.sincos": "\nbase.sincos( [out,] x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n > var out = new Float64Array( 2 );\n > var v = base.sincos( out, 0.0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi\n", - "base.sincospi": "\nbase.sincospi( [out,] x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n > var out = new Float64Array( 2 );\n > var v = base.sincospi( out, 0.0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi\n", - "base.sinh": "\nbase.sinh( x )\n Computes the hyperbolic sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n", - "base.sinpi": "\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n", - "base.spence": "\nbase.spence( x )\n Evaluates Spence’s function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n", - "base.sqrt": "\nbase.sqrt( x )\n Computes the principal square root.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n", - "base.sqrt1pm1": "\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n", - "base.sumSeries": "\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n", - "base.tan": "\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n", - "base.tanh": "\nbase.tanh( x )\n Computes the hyperbolic tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n", - "base.toBinaryString": "\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n", - "base.toBinaryStringf": "\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n", - "base.toBinaryStringUint8": "\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n", - "base.toBinaryStringUint16": "\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n", - "base.toBinaryStringUint32": "\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n", - "base.toWordf": "\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n", - "base.toWords": "\nbase.toWords( [out,] x )\n Splits a floating-point number into a higher order word (unsigned 32-bit\n integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n // Provide an output array:\n > var out = new Uint32Array( 2 );\n > w = base.toWords( out, 3.14e201 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf", - "base.trigamma": "\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n", - "base.trunc": "\nbase.trunc( x )\n Rounds a numeric value toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n", - "base.trunc2": "\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n", - "base.trunc10": "\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n", - "base.truncb": "\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n", - "base.truncn": "\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n", - "base.truncsd": "\nbase.truncsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5 )\n 3.1415\n > y = base.truncsd( 3.14159, 1 )\n 3.0\n > y = base.truncsd( 12368.0, 2 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n", - "base.uimul": "\nbase.uimul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.uimul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n", - "base.uimuldw": "\nbase.uimuldw( [out,] a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.uimuldw( 1, 10 )\n [ 0, 10 ]\n\n See Also\n --------\n base.imuldw, base.uimul\n", - "base.uint32ToInt32": "\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n", - "base.vercos": "\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n", - "base.versin": "\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n", - "base.wrap": "\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n", - "base.xlog1py": "\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n", - "base.xlogy": "\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n", - "base.zeta": "\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n", - "BERNDT_CPS_WAGES_1985": "\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n", - "bifurcate": "\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n", - "bifurcateBy": "\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n", - "bifurcateByAsync": "\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n", - "bifurcateIn": "\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n", - "bifurcateOwn": "\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n", - "binomialTest": "\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n", - "Buffer": "\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n", - "buffer2json": "\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n The returned JSON object has the following properties:\n\n - type: value type\n - data: buffer data as a generic array\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n", - "capitalize": "\ncapitalize( str )\n Capitalizes the first character in a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n", - "capitalizeKeys": "\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n", - "CATALAN": "\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n", - "CBRT_EPS": "\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n", - "chdir": "\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n", - "chi2gof": "\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can be expected frequencies, population probabilities\n summing to one, or a discrete probability distribution name to test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: Array\n Observation frequencies.\n\n y: Array|string\n Expected frequencies (or probabilities) or a discrete probability\n distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p )\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.print()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.print()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts )\n {...}\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda )\n {...}\n\n", - "circarray2iterator": "\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n", - "circularArrayStream": "\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n", - "CircularBuffer": "\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n buf.clear: Function\n Clears the buffer.\n\n buf.count: integer\n Number of elements currently in the buffer.\n\n buf.full: boolean\n Boolean indicating whether the buffer is full.\n\n buf.iterator: Function\n Returns an iterator for iterating over a buffer. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that a\n returned iterator does **not** iterate over partially full buffers.\n\n buf.length: integer\n Buffer length (capacity).\n\n buf.push: Function\n Adds a value to the buffer. If the buffer is full, the method returns\n the removed value; otherwise, the method returns `undefined`.\n\n buf.toArray: Function\n Returns an array of buffer values.\n\n buf.toJSON: Function\n Serializes a circular buffer as JSON.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n See Also\n --------\n FIFO, Stack\n", - "CMUDICT": "\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary\n - phones: manners of articulation for each sound\n - symbols: complete list of ARPABET symbols used by the dictionary\n - vp: verbal pronunciations of punctuation marks\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n", - "complex": "\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n", - "Complex64": "\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 4.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 8.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n See Also\n --------\n complex, Complex128\n", - "COMPLEX64_NUM_BYTES": "\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n", - "Complex128": "\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 8.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 16.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n See Also\n --------\n complex, Complex64\n", - "COMPLEX128_NUM_BYTES": "\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n", - "compose": "\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n", - "composeAsync": "\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n", - "configdir": "\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n", - "conj": "\nconj( z )\n Returns the complex conjugate of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Complex\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n", - "constantFunction": "\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n", - "constantStream": "\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n", - "constructorName": "\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n", - "contains": "\ncontains( val, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `val` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `val` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does not distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n val: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n", - "convertArray": "\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n The function supports the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n arr: Array|TypedArray\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n", - "convertArraySame": "\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n The function supports input arrays having the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n x: Array|TypedArray\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n", - "convertPath": "\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n", - "copy": "\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n", - "copyBuffer": "\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n", - "countBy": "\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n", - "countByAsync": "\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n", - "curry": "\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n", - "curryRight": "\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n", - "cwd": "\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n", - "DALE_CHALL_NEW": "\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n\n Returns\n -------\n out: Array\n List of familiar English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n", - "datasets": "\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n", - "dayOfQuarter": "\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n", - "dayOfYear": "\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n", - "daysInMonth": "\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n", - "daysInYear": "\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n", - "debugSinkStream": "\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n", - "debugStream": "\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n", - "deepEqual": "\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: bool\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n", - "deepGet": "\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n", - "deepHasOwnProp": "\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n", - "deepHasProp": "\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n", - "deepPluck": "\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n", - "deepSet": "\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n", - "defineMemoizedProperty": "\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n", - "defineProperties": "\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n", - "defineProperty": "\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n", - "dirname": "\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n", - "DoublyLinkedList": "\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n", - "doUntil": "\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n", - "doUntilAsync": "\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n", - "doUntilEach": "\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n", - "doUntilEachRight": "\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n", - "doWhile": "\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n", - "doWhileAsync": "\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n", - "doWhileEach": "\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n", - "doWhileEachRight": "\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n", - "E": "\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n", - "emptyStream": "\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n", - "endsWith": "\nendsWith( str, search[, len] )\n Tests if a `string` ends with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` ends with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n", - "enumerableProperties": "\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n", - "enumerablePropertiesIn": "\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n", - "enumerablePropertySymbols": "\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n", - "enumerablePropertySymbolsIn": "\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n", - "ENV": "\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n", - "EPS": "\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n", - "error2json": "\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n", - "EULERGAMMA": "\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n", - "every": "\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n", - "everyBy": "\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n", - "everyByAsync": "\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n", - "everyByRight": "\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n", - "everyByRightAsync": "\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n", - "evil": "\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n", - "exists": "\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n", - "expandContractions": "\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n", - "extname": "\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n", - "fastmath.abs": "\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n", - "fastmath.acosh": "\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n", - "fastmath.ampbm": "\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n", - "fastmath.asinh": "\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n", - "fastmath.atanh": "\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n", - "fastmath.hypot": "\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n", - "fastmath.log2Uint32": "\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n", - "fastmath.max": "\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n", - "fastmath.min": "\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n", - "fastmath.powint": "\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n", - "fastmath.sqrtUint32": "\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n", - "FEMALE_FIRST_NAMES_EN": "\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n", - "FIFO": "\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n", - "find": "\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n", - "flattenArray": "\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: Array\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n", - "flattenObject": "\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n", - "flignerTest": "\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups })\n\n See Also\n --------\n bartlettTest\n", - "FLOAT16_CBRT_EPS": "\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n", - "FLOAT16_EPS": "\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n", - "FLOAT16_EXPONENT_BIAS": "\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n", - "FLOAT16_MAX": "\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n", - "FLOAT16_MAX_SAFE_INTEGER": "\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n", - "FLOAT16_MIN_SAFE_INTEGER": "\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n", - "FLOAT16_NINF": "\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n", - "FLOAT16_NUM_BYTES": "\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n", - "FLOAT16_PINF": "\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n", - "FLOAT16_PRECISION": "\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n", - "FLOAT16_SMALLEST_NORMAL": "\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n", - "FLOAT16_SMALLEST_SUBNORMAL": "\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n", - "FLOAT16_SQRT_EPS": "\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n", - "FLOAT32_CBRT_EPS": "\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566601151848\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n", - "FLOAT32_EPS": "\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n", - "FLOAT32_EXPONENT_BIAS": "\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n", - "FLOAT32_MAX": "\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n", - "FLOAT32_MAX_SAFE_INTEGER": "\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n", - "FLOAT32_MIN_SAFE_INTEGER": "\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n", - "FLOAT32_NINF": "\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n", - "FLOAT32_NUM_BYTES": "\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n", - "FLOAT32_PINF": "\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n", - "FLOAT32_PRECISION": "\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n", - "FLOAT32_SMALLEST_NORMAL": "\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n", - "FLOAT32_SMALLEST_SUBNORMAL": "\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n", - "FLOAT32_SQRT_EPS": "\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n", - "Float32Array": "\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n", - "FLOAT64_EXPONENT_BIAS": "\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n", - "FLOAT64_HIGH_WORD_EXPONENT_MASK": "\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n", - "FLOAT64_HIGH_WORD_SIGNIFICAND_MASK": "\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK\n", - "FLOAT64_MAX": "\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n", - "FLOAT64_MAX_BASE2_EXPONENT": "\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n", - "FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL": "\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n", - "FLOAT64_MAX_BASE10_EXPONENT": "\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n", - "FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL": "\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n", - "FLOAT64_MAX_LN": "\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n", - "FLOAT64_MAX_SAFE_FIBONACCI": "\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n", - "FLOAT64_MAX_SAFE_INTEGER": "\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n", - "FLOAT64_MAX_SAFE_LUCAS": "\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n", - "FLOAT64_MAX_SAFE_NTH_FIBONACCI": "\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n", - "FLOAT64_MAX_SAFE_NTH_LUCAS": "\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n", - "FLOAT64_MIN_BASE2_EXPONENT": "\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n", - "FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL": "\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n", - "FLOAT64_MIN_BASE10_EXPONENT": "\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n", - "FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL": "\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n", - "FLOAT64_MIN_LN": "\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n", - "FLOAT64_MIN_SAFE_INTEGER": "\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n", - "FLOAT64_NUM_BYTES": "\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n", - "FLOAT64_PRECISION": "\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n", - "FLOAT64_SMALLEST_NORMAL": "\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n", - "FLOAT64_SMALLEST_SUBNORMAL": "\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n", - "Float64Array": "\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n", - "forEach": "\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n", - "forEachAsync": "\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n", - "forEachRight": "\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n", - "forEachRightAsync": "\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n", - "forIn": "\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n", - "forOwn": "\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n", - "FOURTH_PI": "\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n", - "FOURTH_ROOT_EPS": "\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n", - "FRB_SF_WAGE_RIGIDITY": "\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n", - "fromCodePoint": "\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n", - "functionName": "\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n", - "functionSequence": "\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n", - "functionSequenceAsync": "\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n", - "GAMMA_LANCZOS_G": "\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n", - "getegid": "\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n", - "geteuid": "\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n", - "getgid": "\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n", - "getGlobal": "\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n", - "getPrototypeOf": "\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n", - "getuid": "\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n", - "GLAISHER": "\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n", - "group": "\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n", - "groupBy": "\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n", - "groupByAsync": "\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n", - "groupIn": "\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n", - "groupOwn": "\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n", - "HALF_LN2": "\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n", - "HALF_PI": "\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n", - "HARRISON_BOSTON_HOUSE_PRICES": "\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n", - "HARRISON_BOSTON_HOUSE_PRICES_CORRECTED": "\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n", - "hasArrayBufferSupport": "\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n", - "hasAsyncAwaitSupport": "\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n", - "hasAsyncIteratorSymbolSupport": "\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n", - "hasClassSupport": "\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n", - "hasDefinePropertiesSupport": "\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n", - "hasDefinePropertySupport": "\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n", - "hasFloat32ArraySupport": "\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n", - "hasFloat64ArraySupport": "\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n", - "hasFunctionNameSupport": "\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n", - "hasGeneratorSupport": "\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n", - "hasInt8ArraySupport": "\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n", - "hasInt16ArraySupport": "\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n", - "hasInt32ArraySupport": "\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n", - "hasIteratorSymbolSupport": "\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n", - "hasMapSupport": "\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n", - "hasNodeBufferSupport": "\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n", - "hasOwnProp": "\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n", - "hasProp": "\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n", - "hasProxySupport": "\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n", - "hasSetSupport": "\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n", - "hasSharedArrayBufferSupport": "\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n", - "hasSymbolSupport": "\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n", - "hasToStringTagSupport": "\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n", - "hasUint8ArraySupport": "\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n", - "hasUint8ClampedArraySupport": "\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n", - "hasUint16ArraySupport": "\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n", - "hasUint32ArraySupport": "\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n", - "hasWeakMapSupport": "\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n", - "hasWeakSetSupport": "\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n", - "hasWebAssemblySupport": "\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n", - "HERNDON_VENUS_SEMIDIAMETERS": "\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n", - "homedir": "\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n", - "HOURS_IN_DAY": "\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n", - "HOURS_IN_WEEK": "\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n", - "hoursInMonth": "\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n", - "hoursInYear": "\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n", - "httpServer": "\nhttpServer( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n createServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var createServer = httpServer()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > createServer = httpServer( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > createServer = httpServer( opts )\n \n\n\ncreateServer( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var createServer = httpServer();\n > createServer( done );\n\n", - "identity": "\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n", - "ifelse": "\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n", - "ifelseAsync": "\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object\n - result: either `x` or `y`\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n", - "ifthen": "\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n", - "ifthenAsync": "\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion\n\n The predicate function callback accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n", - "imag": "\nimag( z )\n Returns the imaginary component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n", - "IMG_ACANTHUS_MOLLIS": "\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n", - "IMG_AIRPLANE_FROM_ABOVE": "\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n", - "IMG_ALLIUM_OREOPHILUM": "\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n", - "IMG_BLACK_CANYON": "\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n", - "IMG_DUST_BOWL_HOME": "\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n", - "IMG_FRENCH_ALPINE_LANDSCAPE": "\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n", - "IMG_LOCOMOTION_HOUSE_CAT": "\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n", - "IMG_LOCOMOTION_NUDE_MALE": "\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n", - "IMG_MARCH_PASTORAL": "\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n", - "IMG_NAGASAKI_BOATS": "\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n", - "incrapcorr": "\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n", - "incrcount": "\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n", - "incrcovariance": "\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n", - "incrcovmat": "\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n", - "incrcv": "\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n", - "increwmean": "\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n", - "increwstdev": "\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n", - "increwvariance": "\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n", - "incrgmean": "\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n", - "incrgrubbs": "\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n", - "incrhmean": "\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n", - "incrkmeans": "\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n", - "incrkurtosis": "\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n", - "incrmaape": "\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n", - "incrmae": "\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n", - "incrmapcorr": "\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n", - "incrmape": "\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n", - "incrmax": "\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n", - "incrmaxabs": "\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n", - "incrmcovariance": "\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n", - "incrmcv": "\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n", - "incrmda": "\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n", - "incrme": "\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n", - "incrmean": "\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n", - "incrmeanabs": "\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n", - "incrmeanabs2": "\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n", - "incrmeanstdev": "\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n", - "incrmeanvar": "\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n", - "incrmgmean": "\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n", - "incrmgrubbs": "\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n", - "incrmhmean": "\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n", - "incrmidrange": "\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n", - "incrmin": "\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n", - "incrminabs": "\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n", - "incrminmax": "\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n", - "incrminmaxabs": "\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n", - "incrmmaape": "\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n", - "incrmmae": "\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n", - "incrmmape": "\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n", - "incrmmax": "\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n", - "incrmmaxabs": "\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n", - "incrmmda": "\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n", - "incrmme": "\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n", - "incrmmean": "\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n", - "incrmmeanabs": "\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n", - "incrmmeanabs2": "\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n", - "incrmmeanstdev": "\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n", - "incrmmeanvar": "\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n", - "incrmmidrange": "\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n", - "incrmmin": "\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n", - "incrmminabs": "\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n", - "incrmminmax": "\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n", - "incrmminmaxabs": "\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n", - "incrmmpe": "\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n", - "incrmmse": "\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n", - "incrmpcorr": "\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n", - "incrmpcorr2": "\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n", - "incrmpcorrdist": "\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n", - "incrmpe": "\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n", - "incrmprod": "\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n", - "incrmrange": "\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n", - "incrmrmse": "\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n", - "incrmrss": "\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n", - "incrmse": "\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n", - "incrmstdev": "\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n", - "incrmsum": "\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n", - "incrmsumabs": "\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n", - "incrmsumabs2": "\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n", - "incrmsummary": "\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n", - "incrmsumprod": "\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n", - "incrmvariance": "\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n", - "incrmvmr": "\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n", - "incrpcorr": "\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n", - "incrpcorr2": "\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n", - "incrpcorrdist": "\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n", - "incrpcorrdistmat": "\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n", - "incrpcorrmat": "\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n", - "incrprod": "\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n", - "incrrange": "\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n", - "incrrmse": "\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n", - "incrrss": "\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n", - "incrskewness": "\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n", - "incrspace": "\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n", - "incrstdev": "\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n", - "incrsum": "\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n", - "incrsumabs": "\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n", - "incrsumabs2": "\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n", - "incrsummary": "\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n", - "incrsumprod": "\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n", - "incrvariance": "\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n", - "incrvmr": "\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n", - "incrwmean": "\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value\n - w: weight\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n", - "ind2sub": "\nind2sub( [out,] shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'wrap', the function wraps around\n a linear index exceeding array dimensions using modulo arithmetic. If\n equal to 'clamp', the function sets a linear index exceeding array\n dimensions to either `0` (minimum linear index) or the maximum linear\n index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n // Provide an output array:\n > var out = new Array( d.length );\n > s = ind2sub( out, d, 17 )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n", - "indexOf": "\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n", - "inherit": "\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n", - "inheritedEnumerableProperties": "\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n", - "inheritedEnumerablePropertySymbols": "\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n", - "inheritedKeys": "\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n", - "inheritedNonEnumerableProperties": "\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n", - "inheritedNonEnumerablePropertyNames": "\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n", - "inheritedNonEnumerablePropertySymbols": "\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n", - "inheritedProperties": "\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n", - "inheritedPropertyDescriptor": "\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n", - "inheritedPropertyDescriptors": "\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n", - "inheritedPropertyNames": "\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n", - "inheritedPropertySymbols": "\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n", - "inheritedWritableProperties": "\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n", - "inheritedWritablePropertyNames": "\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n", - "inheritedWritablePropertySymbols": "\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n", - "inmap": "\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight\n", - "inmapAsync": "\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n", - "inmapRight": "\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap\n", - "inmapRightAsync": "\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n", - "inspectSinkStream": "\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n", - "inspectStream": "\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n", - "instanceOf": "\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n", - "INT8_MAX": "\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n", - "INT8_MIN": "\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n", - "INT8_NUM_BYTES": "\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n", - "Int8Array": "\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n", - "INT16_MAX": "\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n", - "INT16_MIN": "\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n", - "INT16_NUM_BYTES": "\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n", - "Int16Array": "\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n", - "INT32_MAX": "\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n", - "INT32_MIN": "\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n", - "INT32_NUM_BYTES": "\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n", - "Int32Array": "\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n", - "IS_BIG_ENDIAN": "\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n", - "IS_BROWSER": "\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n", - "IS_DARWIN": "\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n", - "IS_ELECTRON": "\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n", - "IS_ELECTRON_MAIN": "\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n", - "IS_ELECTRON_RENDERER": "\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n", - "IS_LITTLE_ENDIAN": "\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n", - "IS_NODE": "\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n", - "IS_WEB_WORKER": "\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n", - "IS_WINDOWS": "\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n", - "isAbsolutePath": "\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n", - "isAccessorProperty": "\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n", - "isAccessorPropertyIn": "\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n", - "isAlphagram": "\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n", - "isAlphaNumeric": "\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n", - "isAnagram": "\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n", - "isArguments": "\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n", - "isArray": "\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n", - "isArrayArray": "\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n", - "isArrayBuffer": "\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n", - "isArrayLength": "\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n", - "isArrayLike": "\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject\n", - "isArrayLikeObject": "\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike\n", - "isASCII": "\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n", - "isBetween": "\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n", - "isBetweenArray": "\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n", - "isBinaryString": "\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n", - "isBoolean": "\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n", - "isBooleanArray": "\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n", - "isBoxedPrimitive": "\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n", - "isBuffer": "\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n", - "isCapitalized": "\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n", - "isCentrosymmetricMatrix": "\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 2, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n", - "isCircular": "\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n", - "isCircularArray": "\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n", - "isCircularPlainObject": "\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n", - "isCollection": "\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike\n", - "isComplex": "\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n", - "isComplex64": "\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n", - "isComplex64Array": "\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n", - "isComplex128": "\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n", - "isComplex128Array": "\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n", - "isComplexLike": "\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n", - "isComplexTypedArray": "\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n", - "isConfigurableProperty": "\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n", - "isConfigurablePropertyIn": "\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n", - "isDataProperty": "\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n", - "isDataPropertyIn": "\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n", - "isDateObject": "\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n", - "isDigitString": "\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n", - "isEmailAddress": "\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n", - "isEmptyArray": "\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray\n", - "isEmptyObject": "\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n", - "isEmptyString": "\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n", - "isEnumerableProperty": "\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n", - "isEnumerablePropertyIn": "\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n", - "isError": "\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n", - "isEvalError": "\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n", - "isEven": "\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n", - "isFalsy": "\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n", - "isFalsyArray": "\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n", - "isFinite": "\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n", - "isFiniteArray": "\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n", - "isFloat32Array": "\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n", - "isFloat64Array": "\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n", - "isFunction": "\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n", - "isFunctionArray": "\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n", - "isGeneratorObject": "\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n", - "isGeneratorObjectLike": "\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n", - "isHexString": "\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n", - "isInfinite": "\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n", - "isInheritedProperty": "\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n", - "isInt8Array": "\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n", - "isInt16Array": "\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n", - "isInt32Array": "\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n", - "isInteger": "\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n", - "isIntegerArray": "\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n", - "isIterableLike": "\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n", - "isIteratorLike": "\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n", - "isJSON": "\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n", - "isLeapYear": "\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n", - "isLowercase": "\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n", - "isMatrixLike": "\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n", - "isMethod": "\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n", - "isMethodIn": "\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n", - "isNamedTypedTupleLike": "\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n", - "isnan": "\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n", - "isNaNArray": "\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n", - "isNativeFunction": "\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n", - "isndarrayLike": "\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n", - "isNegativeInteger": "\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n", - "isNegativeIntegerArray": "\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n", - "isNegativeNumber": "\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n", - "isNegativeNumberArray": "\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n", - "isNegativeZero": "\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n", - "isNodeBuiltin": "\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n", - "isNodeDuplexStreamLike": "\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n", - "isNodeReadableStreamLike": "\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n", - "isNodeREPL": "\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n", - "isNodeStreamLike": "\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n", - "isNodeTransformStreamLike": "\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n", - "isNodeWritableStreamLike": "\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n", - "isNonConfigurableProperty": "\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n", - "isNonConfigurablePropertyIn": "\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n", - "isNonEnumerableProperty": "\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n", - "isNonEnumerablePropertyIn": "\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n", - "isNonNegativeInteger": "\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n", - "isNonNegativeIntegerArray": "\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n", - "isNonNegativeNumber": "\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n", - "isNonNegativeNumberArray": "\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n", - "isNonPositiveInteger": "\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n", - "isNonPositiveIntegerArray": "\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n", - "isNonPositiveNumber": "\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n", - "isNonPositiveNumberArray": "\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n", - "isNonSymmetricMatrix": "\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n", - "isNull": "\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n", - "isNullArray": "\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n", - "isNumber": "\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n", - "isNumberArray": "\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n", - "isNumericArray": "\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n", - "isObject": "\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n", - "isObjectArray": "\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n", - "isObjectLike": "\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n", - "isOdd": "\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n", - "isoWeeksInYear": "\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n", - "isPersymmetricMatrix": "\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n", - "isPlainObject": "\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n", - "isPlainObjectArray": "\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n", - "isPositiveInteger": "\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n", - "isPositiveIntegerArray": "\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n", - "isPositiveNumber": "\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n", - "isPositiveNumberArray": "\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n", - "isPositiveZero": "\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n", - "isPrimitive": "\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n", - "isPrimitiveArray": "\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n", - "isPRNGLike": "\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n", - "isProbability": "\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n", - "isProbabilityArray": "\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n", - "isPrototypeOf": "\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n", - "isRangeError": "\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n", - "isReadableProperty": "\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n", - "isReadablePropertyIn": "\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n", - "isReadOnlyProperty": "\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n", - "isReadOnlyPropertyIn": "\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n", - "isReadWriteProperty": "\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n", - "isReadWritePropertyIn": "\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n", - "isReferenceError": "\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n", - "isRegExp": "\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n", - "isRegExpString": "\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n", - "isRelativePath": "\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n", - "isSafeInteger": "\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n", - "isSafeIntegerArray": "\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n", - "isSameValue": "\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n", - "isSameValueZero": "\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n", - "isSharedArrayBuffer": "\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n", - "isSkewCentrosymmetricMatrix": "\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 2, 1, -1, -2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n", - "isSkewPersymmetricMatrix": "\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 1, 0, 0, -1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n", - "isSkewSymmetricMatrix": "\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 0, -1, 1, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n", - "isSquareMatrix": "\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 0, 0, 0, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n", - "isStrictEqual": "\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n", - "isString": "\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n", - "isStringArray": "\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n", - "isSymbol": "\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n", - "isSymbolArray": "\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n", - "isSymmetricMatrix": "\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 0, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n", - "isSyntaxError": "\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n", - "isTruthy": "\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n", - "isTruthyArray": "\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n", - "isTypedArray": "\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n", - "isTypedArrayLength": "\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n", - "isTypedArrayLike": "\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n", - "isTypeError": "\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n", - "isUint8Array": "\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n", - "isUint8ClampedArray": "\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n", - "isUint16Array": "\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n", - "isUint32Array": "\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n", - "isUNCPath": "\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n", - "isUndefined": "\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n", - "isUndefinedOrNull": "\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n", - "isUnityProbabilityArray": "\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n", - "isUppercase": "\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n", - "isURI": "\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n", - "isURIError": "\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n", - "isVectorLike": "\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n", - "isWhitespace": "\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n RE_WHITESPACE\n", - "isWritableProperty": "\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n", - "isWritablePropertyIn": "\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n", - "isWriteOnlyProperty": "\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n", - "isWriteOnlyPropertyIn": "\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n", - "iterAdd": "\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n", - "iterAdvance": "\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n", - "iterAny": "\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n", - "iterAnyBy": "\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n", - "iterator2array": "\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value\n - index: iterated value index (zero-based)\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n", - "iterator2arrayview": "\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n", - "iterator2arrayviewRight": "\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n", - "iteratorStream": "\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n", - "IteratorSymbol": "\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n", - "iterawgn": "\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n", - "iterawln": "\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n", - "iterawun": "\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n", - "iterBartlettHannPulse": "\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n", - "iterBartlettPulse": "\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n", - "iterConcat": "\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n", - "iterConstant": "\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n", - "iterCosineWave": "\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n", - "iterCounter": "\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n", - "itercugmean": "\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n", - "itercuhmean": "\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n", - "itercumax": "\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n", - "itercumaxabs": "\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n", - "itercumean": "\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n", - "itercumeanabs": "\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n", - "itercumeanabs2": "\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n", - "itercumidrange": "\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n", - "itercumin": "\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n", - "itercuminabs": "\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n", - "itercuprod": "\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n", - "itercurange": "\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n", - "itercusum": "\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n", - "itercusumabs": "\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n", - "itercusumabs2": "\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n", - "iterDedupe": "\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n", - "iterDedupeBy": "\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value\n - sprev: previous source iterated value\n - dprev: previous downstream iterated value\n - index: source iteration index (zero-based)\n - acc: previous resolved value\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n", - "iterDiracComb": "\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n", - "iterDivide": "\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n", - "iterEmpty": "\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n", - "iterEvery": "\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n", - "iterEveryBy": "\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n", - "iterFibonacci": "\niterFibonacci( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacci();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterNonFibonacci\n", - "iterFill": "\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n", - "iterFilter": "\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n", - "iterFilterMap": "\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n", - "iterFirst": "\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n", - "iterFlatTopPulse": "\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n", - "iterFlow": "\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n", - "iterForEach": "\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n", - "iterHannPulse": "\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n", - "iterHead": "\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n", - "iterIntersection": "\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n", - "iterIntersectionByHash": "\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n", - "iterLanczosPulse": "\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n", - "iterLast": "\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n", - "iterLength": "\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n", - "iterMap": "\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n", - "iterMapN": "\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values\n - index: iteration index (zero-based)\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n", - "itermax": "\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n", - "itermaxabs": "\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n", - "itermean": "\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n", - "itermeanabs": "\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n", - "itermeanabs2": "\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n", - "itermidrange": "\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n", - "itermin": "\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n", - "iterminabs": "\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n", - "itermmax": "\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n", - "itermmaxabs": "\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n", - "itermmean": "\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n", - "itermmeanabs": "\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n", - "itermmeanabs2": "\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n", - "itermmidrange": "\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n", - "itermmin": "\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n", - "itermminabs": "\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n", - "iterMod": "\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n", - "itermprod": "\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n", - "itermrange": "\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n", - "itermsum": "\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n", - "itermsumabs": "\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n", - "itermsumabs2": "\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n", - "iterMultiply": "\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n", - "iterNone": "\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n", - "iterNoneBy": "\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n", - "iterNonFibonacci": "\niterNonFibonacci( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacci();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacci\n", - "iterNth": "\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n", - "iterPeriodicSinc": "\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n", - "iterPipeline": "\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n", - "iterPop": "\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n", - "iterprod": "\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n", - "iterPulse": "\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n", - "iterPush": "\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n", - "iterrange": "\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n", - "iterReject": "\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n", - "iterReplicate": "\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n", - "iterReplicateBy": "\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value\n - index: source iteration index (zero-based)\n - n: iteration index (zero-based)\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n", - "iterSawtoothWave": "\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n", - "iterShift": "\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n", - "iterSineWave": "\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n", - "iterSlice": "\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n", - "iterSome": "\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n", - "iterSomeBy": "\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n", - "iterSquareWave": "\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n", - "iterstdev": "\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n", - "iterSubtract": "\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n", - "itersum": "\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n", - "itersumabs": "\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n", - "itersumabs2": "\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n", - "iterThunk": "\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n", - "iterTriangleWave": "\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n", - "iterUnion": "\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n", - "iterUnique": "\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n", - "iterUniqueBy": "\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n", - "iterUniqueByHash": "\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n", - "iterUnshift": "\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n", - "itervariance": "\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n", - "joinStream": "\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n", - "kde2d": "", - "keyBy": "\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n", - "keyByRight": "\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n", - "keysIn": "\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n", - "kruskalTest": "\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups })\n\n", - "kstest": "\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 })\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 })\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' })\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' })\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true })\n { pValue: ~1, statistic: 0.1, ... }\n\n", - "LinkedList": "\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n", - "linspace": "\nlinspace( start, stop[, length] )\n Generates a linearly spaced numeric array.\n\n If a `length` is not provided, the default output array length is `100`.\n\n The output array is guaranteed to include the `start` and `stop` values.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Last array value.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = linspace( 0, 100, 6 )\n [ 0, 20, 40, 60, 80, 100 ]\n\n See Also\n --------\n incrspace, logspace\n", - "LIU_NEGATIVE_OPINION_WORDS_EN": "\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n", - "LIU_POSITIVE_OPINION_WORDS_EN": "\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n", - "LN_HALF": "\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n", - "LN_PI": "\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n", - "LN_SQRT_TWO_PI": "\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n", - "LN_TWO_PI": "\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n", - "LN2": "\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n", - "LN10": "\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n", - "LOG2E": "\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n", - "LOG10E": "\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n", - "logspace": "\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n", - "lowercase": "\nlowercase( str )\n Converts a `string` to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n", - "lowercaseKeys": "\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n", - "lowess": "\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n", - "lpad": "\nlpad( str, len[, pad] )\n Left pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n", - "ltrim": "\nltrim( str )\n Trims whitespace from the beginning of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n trim, rtrim\n", - "MALE_FIRST_NAMES_EN": "\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n", - "mapFun": "\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n", - "mapFunAsync": "\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - `index`: invocation index (starting from zero)\n - `next`: callback to be invoked upon function completion\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n", - "mapKeys": "\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n", - "mapKeysAsync": "\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `key`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `key`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `key`\n - `value`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `key`: transformed key\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n", - "mapValues": "\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n", - "mapValuesAsync": "\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `value`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `value`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `value`\n - `key`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `value`: transformed value\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n", - "MAX_ARRAY_LENGTH": "\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n", - "MAX_TYPED_ARRAY_LENGTH": "\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n", - "memoize": "\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n", - "merge": "\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n", - "MILLISECONDS_IN_DAY": "\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n", - "MILLISECONDS_IN_HOUR": "\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n", - "MILLISECONDS_IN_MINUTE": "\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n", - "MILLISECONDS_IN_SECOND": "\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n", - "MILLISECONDS_IN_WEEK": "\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n", - "MINARD_NAPOLEONS_MARCH": "\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size\n - cities: cities\n - labels: map labels\n - temperature: temperature during the army's return from Russia\n - rivers: river data\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var river = data.river\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n", - "MINUTES_IN_DAY": "\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n", - "MINUTES_IN_HOUR": "\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n", - "MINUTES_IN_WEEK": "\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n", - "minutesInMonth": "\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n", - "minutesInYear": "\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n", - "MOBY_DICK": "\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier)\n - title: chapter title (if available; otherwise, empty)\n - text: chapter text\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n", - "MONTH_NAMES_EN": "\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n", - "MONTHS_IN_YEAR": "\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n", - "moveProperty": "\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n", - "namedtypedtuple": "\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( Float64Array[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...[, elementN]]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element: number\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n", - "nativeClass": "\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n", - "ndarray": "\nndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarray( 'generic', 2 )\n \n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n array\n", - "ndarrayCastingModes": "\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types\n - 'equiv': allow casting between identical and byte swapped types\n - 'safe': only allow \"safe\" casts\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats)\n - 'unsafe': allow casting between all types (including between integers and\n floats)\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n", - "ndarrayDataTypes": "\nndarrayDataTypes()\n Returns a list of ndarray data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n", - "ndarrayIndexModes": "\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n", - "ndarrayMemoized": "\nndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarrayMemoized( 'generic', 2 )\n \n > var f = ndarrayMemoized( 'generic', 2 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n array, ndarray\n", - "ndarrayMinDataType": "\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n", - "ndarrayNextDataType": "\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n", - "ndarrayOrders": "\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n", - "ndarrayPromotionRules": "\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n ndarray data type.\n\n dtype2: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n", - "ndarraySafeCasts": "\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n", - "ndarraySameKindCasts": "\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n", - "NIGHTINGALES_ROSE": "\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son. .\n\n", - "NINF": "\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n", - "NODE_VERSION": "\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n", - "none": "\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n", - "noneBy": "\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n", - "noneByAsync": "\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n", - "noneByRight": "\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n", - "noneByRightAsync": "\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n", - "nonEnumerableProperties": "\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n", - "nonEnumerablePropertiesIn": "\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n", - "nonEnumerablePropertyNames": "\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n", - "nonEnumerablePropertyNamesIn": "\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n", - "nonEnumerablePropertySymbols": "\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n", - "nonEnumerablePropertySymbolsIn": "\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n", - "noop": "\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n", - "now": "\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n", - "NUM_CPUS": "\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n", - "Number": "\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n", - "objectEntries": "\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n", - "objectEntriesIn": "\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n", - "objectFromEntries": "\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n", - "objectInverse": "\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n", - "objectInverseBy": "\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n", - "objectKeys": "\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, objectValues\n", - "objectValues": "\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n", - "objectValuesIn": "\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n", - "omit": "\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n", - "omitBy": "\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n", - "openURL": "\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n", - "PACE_BOSTON_HOUSE_PRICES": "\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number\n - town: town name\n - town_id: town identifier\n - tract: tract identifier\n - lon: longitude\n - lat: latitude\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n", - "pad": "\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' })\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' })\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n", - "papply": "\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n", - "papplyRight": "\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n", - "parallel": "\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n Examples\n --------\n > function done( error ) { if ( error ) { throw error; } };\n > var files = [ './a.js', './b.js' ];\n > parallel( files, done );\n\n // Specify the number of workers:\n > var opts = { 'workers': 8 };\n > parallel( files, opts, done );\n\n", - "parseJSON": "\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n", - "PATH_DELIMITER": "\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n", - "PATH_DELIMITER_POSIX": "\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n", - "PATH_DELIMITER_WIN32": "\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n", - "PATH_SEP": "\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n", - "PATH_SEP_POSIX": "\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n", - "PATH_SEP_WIN32": "\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n", - "pcorrtest": "\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n", - "percentEncode": "\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n", - "PHI": "\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n", - "PI": "\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n", - "PI_SQUARED": "\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n", - "pick": "\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n", - "pickBy": "\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n", - "PINF": "\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n", - "pkg2alias": "\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n", - "pkg2related": "\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n", - "PLATFORM": "\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n", - "plot": "\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n", - "Plot": "\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n", - "pluck": "\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n", - "pop": "\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n", - "prepend": "\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n", - "properties": "\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n", - "propertiesIn": "\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n", - "propertyDescriptor": "\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n", - "propertyDescriptorIn": "\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n", - "propertyDescriptors": "\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n", - "propertyDescriptorsIn": "\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n", - "propertyNames": "\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n", - "propertyNamesIn": "\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n", - "propertySymbols": "\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n", - "propertySymbolsIn": "\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n", - "Proxy": "\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n", - "push": "\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n", - "quarterOfYear": "\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n", - "random.iterators.arcsine": "\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n", - "random.iterators.bernoulli": "\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n", - "random.iterators.beta": "\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n", - "random.iterators.betaprime": "\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n", - "random.iterators.binomial": "\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n", - "random.iterators.boxMuller": "\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n", - "random.iterators.cauchy": "\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n", - "random.iterators.chi": "\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n", - "random.iterators.chisquare": "\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n", - "random.iterators.cosine": "\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n", - "random.iterators.discreteUniform": "\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n", - "random.iterators.erlang": "\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n", - "random.iterators.exponential": "\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n", - "random.iterators.f": "\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n", - "random.iterators.frechet": "\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n", - "random.iterators.gamma": "\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n", - "random.iterators.geometric": "\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n", - "random.iterators.gumbel": "\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n", - "random.iterators.hypergeometric": "\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n", - "random.iterators.improvedZiggurat": "\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n", - "random.iterators.invgamma": "\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n", - "random.iterators.kumaraswamy": "\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n", - "random.iterators.laplace": "\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n", - "random.iterators.levy": "\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n", - "random.iterators.logistic": "\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n", - "random.iterators.lognormal": "\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n", - "random.iterators.minstd": "\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n", - "random.iterators.minstdShuffle": "\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n", - "random.iterators.mt19937": "\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n", - "random.iterators.negativeBinomial": "\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n", - "random.iterators.normal": "\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n", - "random.iterators.pareto1": "\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n", - "random.iterators.poisson": "\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n", - "random.iterators.randi": "\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n", - "random.iterators.randn": "\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n", - "random.iterators.randu": "\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n", - "random.iterators.rayleigh": "\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n", - "random.iterators.t": "\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n", - "random.iterators.triangular": "\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n", - "random.iterators.uniform": "\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n", - "random.iterators.weibull": "\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n", - "random.streams.arcsine": "\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n", - "random.streams.bernoulli": "\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n", - "random.streams.beta": "\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n", - "random.streams.betaprime": "\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n", - "random.streams.binomial": "\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n", - "random.streams.boxMuller": "\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n", - "random.streams.cauchy": "\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n", - "random.streams.chi": "\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n", - "random.streams.chisquare": "\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n", - "random.streams.cosine": "\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n", - "random.streams.discreteUniform": "\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n", - "random.streams.erlang": "\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n", - "random.streams.exponential": "\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n", - "random.streams.f": "\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n", - "random.streams.gamma": "\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n", - "random.streams.geometric": "\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n", - "random.streams.gumbel": "\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n", - "random.streams.improvedZiggurat": "\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n", - "random.streams.invgamma": "\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n", - "random.streams.kumaraswamy": "\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n", - "random.streams.laplace": "\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n", - "random.streams.levy": "\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n", - "random.streams.logistic": "\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n", - "random.streams.lognormal": "\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n", - "random.streams.minstd": "\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n", - "random.streams.minstdShuffle": "\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n", - "random.streams.mt19937": "\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n", - "random.streams.negativeBinomial": "\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n", - "random.streams.normal": "\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n", - "random.streams.pareto1": "\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n", - "random.streams.poisson": "\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n", - "random.streams.randi": "\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n", - "random.streams.randn": "\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n", - "random.streams.randu": "\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n", - "random.streams.rayleigh": "\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n", - "random.streams.t": "\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n", - "random.streams.uniform": "\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n", - "random.streams.weibull": "\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n", - "ranks": "\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n", - "RE_BASENAME": "\nRE_BASENAME\n Regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_BASENAME.posix\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nRE_BASENAME.win32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n RE_BASENAME_POSIX, RE_BASENAME_WINDOWS\n", - "RE_BASENAME_POSIX": "\nRE_BASENAME_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_BASENAME, RE_BASENAME_WINDOWS\n", - "RE_BASENAME_WINDOWS": "\nRE_BASENAME_WINDOWS\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_BASENAME, RE_BASENAME_POSIX\n", - "RE_COLOR_HEXADECIMAL": "\nRE_COLOR_HEXADECIMAL\n Regular expression to match a hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.test( '000' )\n false\n > bool = RE_COLOR_HEXADECIMAL.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.shorthand\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'ffffff' )\n false\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.either\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.either.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( 'beep' )\n false\n\n", - "RE_DECIMAL_NUMBER": "\nRE_DECIMAL_NUMBER\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var bool = RE_DECIMAL_NUMBER.test( '1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '-1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0' )\n false\n > bool = RE_DECIMAL_NUMBER.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = new RegExp( RE_DECIMAL_NUMBER.source, 'g' );\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\n", - "RE_DIRNAME": "\nRE_DIRNAME\n Regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_DIRNAME.posix\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nRE_DIRNAME.win32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\\\foo\\\\bar'\n\n See Also\n --------\n RE_DIRNAME_POSIX, RE_DIRNAME_WINDOWS, dirname\n", - "RE_DIRNAME_POSIX": "\nRE_DIRNAME_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( './' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_DIRNAME, RE_DIRNAME_WINDOWS, dirname\n", - "RE_DIRNAME_WINDOWS": "\nRE_DIRNAME_WINDOWS\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\\\foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\\\foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_DIRNAME, RE_DIRNAME_POSIX, dirname\n", - "RE_EOL": "\nRE_EOL\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\n", - "RE_EXTENDED_LENGTH_PATH": "\nRE_EXTENDED_LENGTH_PATH\n Regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Examples\n --------\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n\n", - "RE_EXTNAME": "\nRE_EXTNAME\n Regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_EXTNAME.posix\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nRE_EXTNAME.win32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n RE_EXTNAME_POSIX, RE_EXTNAME_WINDOWS, extname\n", - "RE_EXTNAME_POSIX": "\nRE_EXTNAME_POSIX\n Regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( '.' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( './' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_EXTNAME, RE_EXTNAME_WINDOWS, extname\n", - "RE_EXTNAME_WINDOWS": "\nRE_EXTNAME_WINDOWS\n Regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE_EXTNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_EXTNAME, RE_EXTNAME_POSIX, extname\n", - "RE_FILENAME": "\nRE_FILENAME\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_FILENAME.posix\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nRE_FILENAME.win32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n RE_FILENAME_POSIX, RE_FILENAME_WINDOWS\n", - "RE_FILENAME_POSIX": "\nRE_FILENAME_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_POSIX.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_POSIX.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( './' ).slice()\n [ './', '', '.', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n See Also\n --------\n RE_FILENAME, RE_FILENAME_WINDOWS\n", - "RE_FILENAME_WINDOWS": "\nRE_FILENAME_WINDOWS\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( './' ).slice()\n [ './', '', '', '.', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n See Also\n --------\n RE_FILENAME, RE_FILENAME_POSIX\n", - "RE_FUNCTION_NAME": "\nRE_FUNCTION_NAME\n Regular expression to capture a function name.\n\n Examples\n --------\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n See Also\n --------\n functionName\n", - "RE_NATIVE_FUNCTION": "\nRE_NATIVE_FUNCTION\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = RE_NATIVE_FUNCTION.test( Date.toString() )\n true\n > bool = RE_NATIVE_FUNCTION.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n RE_FUNCTION_NAME, functionName\n", - "RE_REGEXP": "\nRE_REGEXP\n Regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Examples\n --------\n > var bool = RE_REGEXP.test( '/^beep$/' )\n true\n > bool = RE_REGEXP.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE_REGEXP.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE_REGEXP.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n See Also\n --------\n reFromString\n", - "RE_UNC_PATH": "\nRE_UNC_PATH\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '//server/share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = './foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE_UNC_PATH.test( path )\n false\n\n See Also\n --------\n isUNCPath\n", - "RE_UTF16_SURROGATE_PAIR": "\nRE_UTF16_SURROGATE_PAIR\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var bool = RE_UTF16_SURROGATE_PAIR.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE_UTF16_SURROGATE_PAIR.test( 'abcdef' )\n false\n\n See Also\n --------\n RE_UTF16_UNPAIRED_SURROGATE\n", - "RE_UTF16_UNPAIRED_SURROGATE": "\nRE_UTF16_UNPAIRED_SURROGATE\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var bool = RE_UTF16_UNPAIRED_SURROGATE.test( 'abc' )\n false\n > bool = RE_UTF16_UNPAIRED_SURROGATE.test( '\\uD800' )\n true\n\n See Also\n --------\n RE_UTF16_SURROGATE_PAIR\n", - "RE_WHITESPACE": "\nRE_WHITESPACE\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var bool = RE_WHITESPACE.test( '\\n' )\n true\n > bool = RE_WHITESPACE.test( ' ' )\n true\n > bool = RE_WHITESPACE.test( 'a' )\n false\n\n See Also\n --------\n isWhitespace\n", - "readDir": "\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n", - "readFile": "\nreadFile( file[, options,] clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, readDir, readJSON, writeFile\n", - "readFileList": "\nreadFileList( filepaths[, options,] clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path\n - data: file contents as either a Buffer or string\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n", - "readJSON": "\nreadJSON( file[, options,] clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n", - "readWASM": "\nreadWASM( file, [options,] clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n", - "real": "\nreal( z )\n Returns the real component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n", - "realmax": "\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n", - "realmin": "\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n", - "reduce": "\nreduce( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) { return acc + v; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduce( arr, 0, sum )\n 6.0\n\n See Also\n --------\n forEach, reduceAsync, reduceRight\n", - "reduceAsync": "\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n", - "reduceRight": "\nreduceRight( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) {\n ... console.log( '%s: %d', acc, v );\n ... return acc + v;\n ... };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduceRight( arr, 0, sum );\n 2: 3.0\n 1: 2.0\n 0: 1.0\n > out\n 6.0\n\n See Also\n --------\n forEachRight, reduce, reduceRightAsync\n", - "reduceRightAsync": "\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n", - "reFromString": "\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n", - "reim": "\nreim( z )\n Returns the real and imaginary components of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n", - "removeFirst": "\nremoveFirst( str )\n Removes the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n\n See Also\n --------\n removeLast\n", - "removeLast": "\nremoveLast( str )\n Removes the last character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n\n See Also\n --------\n removeFirst\n", - "removePunctuation": "\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n", - "removeUTF8BOM": "\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n", - "removeWords": "\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n", - "rename": "\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n", - "reorderArguments": "\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n reverseArguments\n", - "repeat": "\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n", - "replace": "\nreplace( str, search, newval )\n Replaces `search` occurrences with a replacement `string`.\n\n When provided a `string` as the `search` value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n", - "rescape": "\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\\\[A\\\\-Z\\\\]\\\\*'\n\n", - "resolveParentPath": "\nresolveParentPath( path[, options,] clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n", - "reverseArguments": "\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n reorderArguments\n", - "reverseString": "\nreverseString( str )\n Reverses a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n", - "reviveBasePRNG": "\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n", - "reviveBuffer": "\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer)\n - data: buffer data as an array of integers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n", - "reviveComplex": "\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\")\n - re: real component (number)\n - im: imaginary component (number)\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n", - "reviveComplex64": "\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n", - "reviveComplex128": "\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n", - "reviveError": "\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n", - "reviveTypedArray": "\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\")\n - data: typed array data as an array of numbers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n", - "rpad": "\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n", - "rtrim": "\nrtrim( str )\n Trims whitespace from the end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n ltrim, trim\n", - "safeintmax": "\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n", - "safeintmin": "\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n", - "sample": "\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 })\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 })\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 })\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false })\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs })\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false })\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 });\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 });\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n", - "SAVOY_STOPWORDS_FIN": "\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n", - "SAVOY_STOPWORDS_FR": "\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n", - "SAVOY_STOPWORDS_GER": "\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n", - "SAVOY_STOPWORDS_IT": "\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n", - "SAVOY_STOPWORDS_POR": "\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n", - "SAVOY_STOPWORDS_SP": "\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n", - "SAVOY_STOPWORDS_SWE": "\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n", - "SECONDS_IN_DAY": "\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n", - "SECONDS_IN_HOUR": "\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n", - "SECONDS_IN_MINUTE": "\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n", - "SECONDS_IN_WEEK": "\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n", - "secondsInMonth": "\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n", - "secondsInYear": "\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n", - "setConfigurableReadOnly": "\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n", - "setConfigurableReadOnlyAccessor": "\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n", - "setConfigurableReadWriteAccessor": "\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n", - "setConfigurableWriteOnlyAccessor": "\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n", - "setMemoizedReadOnly": "\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n", - "setNonEnumerableProperty": "\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", - "setNonEnumerableReadOnly": "\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n", - "setNonEnumerableReadOnlyAccessor": "\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n", - "setNonEnumerableReadWriteAccessor": "\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n", - "setNonEnumerableWriteOnlyAccessor": "\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n", - "setReadOnly": "\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n", - "setReadOnlyAccessor": "\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n", - "setReadWriteAccessor": "\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n", - "setWriteOnlyAccessor": "\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n", - "SharedArrayBuffer": "\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n", - "shift": "\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n", - "shuffle": "\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' });\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' });\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n", - "sizeOf": "\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - complex128: 128-bit complex numbers\n - complex64: 64-bit complex numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n", - "some": "\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n", - "someBy": "\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n", - "someByAsync": "\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n", - "someByRight": "\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n", - "someByRightAsync": "\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n", - "SOTU": "\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year\n - name: President name\n - party: the President's political party\n - text: speech text\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n", - "SPACHE_REVISED": "\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n", - "SPAM_ASSASSIN": "\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group)\n - group: message group\n - checksum: object containing checksum info\n - text: message text (including headers)\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages)\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages)\n - hard-ham-1: harder to detect non-spam e-mails (250 messages)\n - spam-1: spam e-mails (500 messages)\n - spam-2: spam e-mails collected at a later date (1396 messages)\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5)\n - value: checksum value\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n", - "SparklineBase": "\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n", - "sparsearray2iterator": "\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n", - "sparsearray2iteratorRight": "\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n", - "splitStream": "\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n", - "SQRT_EPS": "\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n", - "SQRT_HALF": "\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n", - "SQRT_HALF_PI": "\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n", - "SQRT_PHI": "\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n", - "SQRT_PI": "\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n", - "SQRT_THREE": "\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n", - "SQRT_TWO": "\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n", - "SQRT_TWO_PI": "\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n", - "Stack": "\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n", - "startcase": "\nstartcase( str )\n Capitalizes the first letter of each word in an input `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n", - "startsWith": "\nstartsWith( str, search[, position] )\n Tests if a `string` starts with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` starts with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n", - "STOPWORDS_EN": "\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n", - "stridedarray2iterator": "\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n", - "stridedArrayStream": "\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n", - "string2buffer": "\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n", - "sub2ind": "\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'wrap', the function wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n", - "SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK": "\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n", - "SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK": "\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n", - "Symbol": "\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n", - "tabulate": "\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n", - "tabulateBy": "\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n", - "tabulateByAsync": "\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n", - "tic": "\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n", - "timeit": "\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` options is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n", - "tmpdir": "\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n", - "toc": "\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n", - "tokenize": "\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n", - "transformStream": "\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n", - "trim": "\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n", - "trycatch": "\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n", - "trycatchAsync": "\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - result: function result\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object\n - result: either the result of `x` or the provided argument `y`\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n", - "tryFunction": "\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n", - "tryRequire": "\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n", - "trythen": "\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n", - "trythenAsync": "\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n", - "ttest": "\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 });\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n", - "ttest2": "\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' });\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' })\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n", - "TWO_PI": "\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n", - "typedarray": "\ntypedarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n", - "typedarray2json": "\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type\n - data: typed array data as a generic array\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n", - "typedarrayComplexCtors": "\ntypedarrayComplexCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayComplexCtors( 'complex64' )\n \n > ctor = typedarrayComplexCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors\n", - "typedarrayComplexDataTypes": "\ntypedarrayComplexDataTypes()\n Returns a list of complex typed array data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = typedarrayComplexDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, ndarrayDataTypes\n", - "typedarrayCtors": "\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n", - "typedarrayDataTypes": "\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n", - "typedarraypool": "\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n", - "typemax": "\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n", - "typemin": "\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n", - "typeOf": "\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n", - "UINT8_MAX": "\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n", - "UINT8_NUM_BYTES": "\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n", - "Uint8Array": "\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n", - "Uint8ClampedArray": "\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n", - "UINT16_MAX": "\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n", - "UINT16_NUM_BYTES": "\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n", - "Uint16Array": "\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n", - "UINT32_MAX": "\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n", - "UINT32_NUM_BYTES": "\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n", - "Uint32Array": "\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n", - "umask": "\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - `+`: enable\n - `-`: disable\n - `=`: enable specified and disable unspecified permissions\n\n For example,\n\n - `u-w`: disable user write permissions\n - `u+w`: enable user write permissions\n - `u=w`: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n", - "uncapitalize": "\nuncapitalize( str )\n Lowercases the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n", - "uncapitalizeKeys": "\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n", - "uncurry": "\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n", - "uncurryRight": "\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n", - "UNICODE_MAX": "\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n", - "UNICODE_MAX_BMP": "\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n", - "UnicodeColumnChartSparkline": "\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n", - "UnicodeLineChartSparkline": "\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n", - "UnicodeSparkline": "\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n", - "UnicodeTristateChartSparkline": "\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n", - "UnicodeUpDownChartSparkline": "\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n", - "UnicodeWinLossChartSparkline": "\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n", - "unlink": "\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n", - "unshift": "\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n", - "until": "\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n", - "untilAsync": "\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n", - "untilEach": "\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n", - "untilEachRight": "\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n", - "unzip": "\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n", - "uppercase": "\nuppercase( str )\n Converts a `string` to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n", - "uppercaseKeys": "\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n", - "US_STATES_ABBR": "\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n", - "US_STATES_CAPITALS": "\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n", - "US_STATES_CAPITALS_NAMES": "\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n", - "US_STATES_NAMES": "\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n", - "US_STATES_NAMES_CAPITALS": "\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n", - "utf16ToUTF8Array": "\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n", - "vartest": "\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n", - "waterfall": "\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n", - "whileAsync": "\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n", - "whileEach": "\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n", - "whileEachRight": "\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n", - "whilst": "\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n", - "writableProperties": "\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n", - "writablePropertiesIn": "\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n", - "writablePropertyNames": "\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n", - "writablePropertyNamesIn": "\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n", - "writablePropertySymbols": "\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n", - "writablePropertySymbolsIn": "\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n", - "writeFile": "\nwriteFile( file, data[, options,] clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n", - "zip": "\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n", - "ztest": "\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 });\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' })\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' })\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n", - "ztest2": "\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 })\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n" -}; - -module.exports = db; diff --git a/lib/node_modules/@stdlib/repl/help/lib/index.js b/lib/node_modules/@stdlib/repl/help/lib/index.js index cbfa2c381bd3..30d29a14bc3d 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/index.js +++ b/lib/node_modules/@stdlib/repl/help/lib/index.js @@ -19,15 +19,15 @@ 'use strict'; /** -* REPL help texts. +* Return the help text associated with a provided alias. * * @module @stdlib/repl/help * * @example * var help = require( '@stdlib/repl/help' ); * -* var o = help(); -* // returns {...} +* var txt = help( 'base.sin' ); +* // returns */ // MODULES // diff --git a/lib/node_modules/@stdlib/repl/help/lib/main.js b/lib/node_modules/@stdlib/repl/help/lib/main.js index dcfe23c93bff..9f2a4dcde0ca 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/main.js +++ b/lib/node_modules/@stdlib/repl/help/lib/main.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -20,23 +20,32 @@ // MODULES // -var copy = require( '@stdlib/utils/copy' ); -var HELP = require( './db.js' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var ALIAS_TO_HELP = require( './../data/data.json' ); // MAIN // /** -* Returns REPL help texts. +* Returns help text associated with a specified alias. * -* @returns {Object} docs +* @param {string} alias - alias +* @throws {TypeError} must provide a string +* @returns {(string|null)} help text * * @example -* var o = help(); -* // returns {...} +* var txt = help( 'base.sin' ); +* // returns */ -function help() { - return copy( HELP ); +function help( alias ) { + if ( !isString( alias ) ) { + throw new TypeError( 'invalid argument. Must provide a string. Value: `' + alias + '`.' ); + } + if ( hasOwnProp( ALIAS_TO_HELP, alias ) ) { + return ALIAS_TO_HELP[ alias ]; + } + return null; } diff --git a/lib/node_modules/@stdlib/repl/help/package.json b/lib/node_modules/@stdlib/repl/help/package.json index c4344ffaee23..e767eb6335d2 100644 --- a/lib/node_modules/@stdlib/repl/help/package.json +++ b/lib/node_modules/@stdlib/repl/help/package.json @@ -13,14 +13,20 @@ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" } ], + "bin": { + "stdlib-help-text": "./bin/cli" + }, "main": "./lib", "directories": { "benchmark": "./benchmark", + "bin": "./bin", + "data": "./data", + "doc": "./docs", "example": "./examples", "lib": "./lib", - "scripts": "./scripts", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { diff --git a/lib/node_modules/@stdlib/repl/help/scripts/build.js b/lib/node_modules/@stdlib/repl/help/scripts/build.js index c4403ce44019..2dc1bec33159 100644 --- a/lib/node_modules/@stdlib/repl/help/scripts/build.js +++ b/lib/node_modules/@stdlib/repl/help/scripts/build.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -28,41 +28,27 @@ var objectKeys = require( '@stdlib/utils/keys' ); var readFile = require( '@stdlib/fs/read-file' ).sync; var readJSON = require( '@stdlib/fs/read-json' ).sync; var writeFile = require( '@stdlib/fs/write-file' ).sync; -var licenseHeader = require( '@stdlib/_tools/licenses/header' ); var resolveParentPath = require( '@stdlib/fs/resolve-parent-path' ).sync; var dirname = require( '@stdlib/utils/dirname' ); var replace = require( '@stdlib/string/replace' ); var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var namespace = require( '@stdlib/namespace' ); +var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); // VARIABLES // var debug = logger( 'repl:help:build' ); -// Create a namespace: -var NAMESPACE = namespace(); - // Filepath convention for REPL text: var REPL_TEXT = 'docs/repl.txt'; // Root search directory: var ROOT = resolvePath( __dirname, '..', '..', '..' ); -// Help docs output file path: -var HELP_OUTPUT = resolvePath( __dirname, '..', 'lib', 'db.js' ); - -// License header options: -var HEADER_OPTIONS = { - 'copyright': 'The Stdlib Authors', - 'year': ( new Date() ).getFullYear() -}; - -// Output file preamble: -var PREAMBLE = '/* eslint-disable quotes, max-lines */\n\n'+licenseHeader( 'Apache-2.0', 'js', HEADER_OPTIONS )+'\n/*\n* This file is generated by scripts/build.js.\n*/\n\'use strict\';\n\nvar db = '; - -// Output file append: -var APPEND = 'module.exports = db;\n'; +// Output file paths: +var OUTPUT_JSON = resolvePath( __dirname, '..', 'data', 'data.json' ); +var OUTPUT_CSV = resolvePath( __dirname, '..', 'data', 'data.csv' ); // Identifier for inserting 'See Also' links: var SEE_ALSO = '\n See Also\n --------\n'; @@ -76,31 +62,12 @@ var RE_ALIAS = /\{\{alias:([^}]+)\}\}/; // FUNCTIONS // -/** -* Generates a hash mapping paths to aliases. -* -* @private -* @returns {Object} hash mapping paths to aliases -*/ -function aliasMap() { - var pkg; - var out; - var i; - - out = {}; - for ( i = 0; i < NAMESPACE.length; i++ ) { - pkg = NAMESPACE[ i ]; - out[ pkg.path ] = pkg.alias; - } - return out; -} - /** * Returns an array of unique items. * * @private -* @param {StringArray} arr - input array of strings -* @returns {StringArray} array containing only unique items +* @param {Array} arr - input array +* @returns {Array} array containing only unique items */ function unique( arr ) { var obj; @@ -116,44 +83,46 @@ function unique( arr ) { } /** -* Generates a hash for REPL help text. +* Main execution sequence. * * @private */ -function createHelp() { +function main() { var related; - var aliases; var fpath; var alias; var ropts; var fopts; + var keys; + var json; var file; var pkg; - var out; var len; var tmp; + var csv; + var ns; var a; var p; var i; var j; + debug( 'Generating REPL help documentation.' ); + ns = namespace(); + ropts = { 'basedir': ROOT }; - debug( 'Package resolve options: %s', JSON.stringify( ropts ) ); - fopts = { 'encoding': 'utf8' }; + debug( 'Package resolve options: %s', JSON.stringify( ropts ) ); - aliases = aliasMap(); - - out = {}; - for ( i = 0; i < NAMESPACE.length; i++ ) { - alias = NAMESPACE[ i ].alias; + json = {}; + for ( i = 0; i < ns.length; i++ ) { + alias = ns[ i ].alias; debug( 'Resolving `%s`', alias ); - fpath = resolve( NAMESPACE[ i ].path, ropts ); + fpath = resolve( ns[ i ].path, ropts ); debug( 'Resolved module path: %s', fpath ); debug( 'Resolving package information.' ); @@ -171,8 +140,8 @@ function createHelp() { continue; } debug( 'Checking package information.' ); - if ( pkg.name !== NAMESPACE[ i ].path ) { - debug( 'Package information does not match path. Expected: %s. Actual: %s.', NAMESPACE[ i ].path, pkg.name ); + if ( pkg.name !== ns[ i ].path ) { + debug( 'Package information does not match path. Expected: %s. Actual: %s.', ns[ i ].path, pkg.name ); continue; } fpath = join( dirname( fpath ), REPL_TEXT ); @@ -195,8 +164,8 @@ function createHelp() { tmp = unique( tmp ); for ( j = 0; j < tmp.length; j++ ) { p = RE_ALIAS.exec( tmp[ j ] )[ 1 ]; // extracts a package identifier - a = aliases[ p ]; - if ( a === void 0 ) { + a = alias2pkg( p ); + if ( a === null ) { debug( 'Unable to resolve alias: %s.', p ); console.warn( 'WARNING: unable to resolve alias `%s` for `%s`. ', p, alias ); // eslint-disable-line no-console } else { @@ -206,13 +175,13 @@ function createHelp() { } } debug( 'Resolving related aliases.' ); - len = NAMESPACE[ i ].related.length; + len = ns[ i ].related.length; if ( len ) { tmp = []; - related = NAMESPACE[ i ].related; + related = ns[ i ].related; for ( j = 0; j < len; j++ ) { - a = aliases[ related[ j ] ]; - if ( a === void 0 ) { + a = alias2pkg( related[ j ] ); + if ( a === null ) { debug( 'Unable to resolve related alias: %s.', related[ j ] ); console.warn( 'WARNING: unable to resolve related alias `%s` for `%s`. ', related[ j ], alias ); // eslint-disable-line no-console } else { @@ -229,21 +198,20 @@ function createHelp() { file = replace( file, SEE_ALSO, '' ); } debug( 'Successfully processed `%s`.', alias ); - out[ alias ] = file; + json[ alias ] = file; } - debug( 'Writing REPL text hash to file.' ); - out = PREAMBLE+JSON.stringify( out, null, '\t' )+';\n\n'+APPEND; - writeFile( HELP_OUTPUT, out, fopts ); -} - -/** -* Main execution sequence. -* -* @private -*/ -function main() { - debug( 'Generating REPL help documentation.' ); - createHelp(); + debug( 'Writing to JSON file.' ); + writeFile( OUTPUT_JSON, JSON.stringify( json ), fopts ); + + debug( 'Writing to CSV file.' ); + keys = objectKeys( json ); + csv = ''; + for ( i = 0; i < keys.length; i++ ) { + tmp = replace( json[ tmp[i] ], /\r?\n/g, '\\n' ); + tmp = replace( tmp, '"', '\\"' ); + csv += keys[ i ] + ',"' + tmp + '"\n'; // Note: ensures trailing newline + } + writeFile( OUTPUT_CSV, csv, fopts ); } diff --git a/lib/node_modules/@stdlib/repl/help/test/test.cli.js b/lib/node_modules/@stdlib/repl/help/test/test.cli.js new file mode 100644 index 000000000000..99e09add5873 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/help/test/test.cli.js @@ -0,0 +1,184 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var exec = require( 'child_process' ).exec; +var tape = require( 'tape' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); +var readFileSync = require( '@stdlib/fs/read-file' ).sync; + + +// VARIABLES // + +var fpath = resolve( __dirname, '..', 'bin', 'cli' ); +var opts = { + 'skip': IS_BROWSER || IS_WINDOWS +}; + + +// FIXTURES // + +var PKG_VERSION = require( './../package.json' ).version; + + +// TESTS // + +tape( 'command-line interface', function test( t ) { + t.ok( true, __filename ); + t.end(); +}); + +tape( 'when invoked with a `--help` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '--help' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-h` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '-h' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `--version` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '--version' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-V` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '-V' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'the command-line interface prints help text', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + 'base.sin' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + stdout = stdout.toString().split( '\n' ); + + // Greater than 1 in order to include the trailing newline: + t.strictEqual( stdout.length > 1, true, 'prints help text' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + } + t.end(); + } +}); + +tape( 'if unable to resolve help text, the command-line interface sets a non-zero exit code', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + 'fjaldfjadljfeoejreandfljasdfjadsfjs' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.pass( error.message ); + t.strictEqual( error.code, 1, 'expected exit code' ); + } + t.strictEqual( stdout.toString(), '', 'does not print to` stdout`' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + t.end(); + } +}); diff --git a/lib/node_modules/@stdlib/repl/help/test/test.js b/lib/node_modules/@stdlib/repl/help/test/test.js index da9f88f3908f..91e411c20c96 100644 --- a/lib/node_modules/@stdlib/repl/help/test/test.js +++ b/lib/node_modules/@stdlib/repl/help/test/test.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -21,7 +21,8 @@ // MODULES // var tape = require( 'tape' ); -var isPlainObject = require( '@stdlib/assert/is-plain-object' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var DATA = require( './../data/data.json' ); var help = require( './../lib' ); @@ -33,16 +34,60 @@ tape( 'main export is a function', function test( t ) { t.end(); }); -tape( 'the function returns an object containing REPL help texts', function test( t ) { - var o1; - var o2; +tape( 'the function throws an error if not provided a string', function test( t ) { + var values; + var i; - o1 = help(); - t.strictEqual( isPlainObject( o1 ), true, 'returns an object' ); + values = [ + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + help( value ); + }; + } +}); + +tape( 'the function returns help text', function test( t ) { + var expected; + var actual; + var list; + var i; + + list = aliases(); + for ( i = 0; i < list.length; i++ ) { + expected = DATA[ list[i] ]; + actual = help( list[i] ); + t.strictEqual( typeof actual, 'string', 'returns a string' ); + t.strictEqual( actual, expected, 'returns expected value for '+list[i] ); + } + t.end(); +}); - o2 = help(); - t.strictEqual( isPlainObject( o2 ), true, 'returns an object' ); - t.notEqual( o1, o2, 'returns new reference' ); +tape( 'the function returns `null` if provided an unrecognized alias', function test( t ) { + var values; + var i; + values = [ + 'adfkaljdfdsafs', + 'adklfadjflajdslfjalsdf', + 'adflkajdlkfjasdlkfjsadlkfjlasdjflsdjfla' + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( help( values[ i ] ), null, 'returns expected value' ); + } t.end(); }); From 68c50edea78ff73d0506dc4342fc7be5c0939b04 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 18:39:06 -0700 Subject: [PATCH 110/142] Fix missing `types` fields --- lib/node_modules/@stdlib/namespace/alias2pkg/package.json | 1 + lib/node_modules/@stdlib/namespace/alias2related/package.json | 1 + lib/node_modules/@stdlib/namespace/aliases/package.json | 1 + lib/node_modules/@stdlib/namespace/pkg2alias/package.json | 1 + lib/node_modules/@stdlib/namespace/pkg2related/package.json | 1 + 5 files changed, 5 insertions(+) diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/package.json b/lib/node_modules/@stdlib/namespace/alias2pkg/package.json index 4d3c9b474b52..b6f5fa9029a2 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/package.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/package.json @@ -26,6 +26,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { diff --git a/lib/node_modules/@stdlib/namespace/alias2related/package.json b/lib/node_modules/@stdlib/namespace/alias2related/package.json index 6537540fd11b..424f8f90550f 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/package.json +++ b/lib/node_modules/@stdlib/namespace/alias2related/package.json @@ -26,6 +26,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { diff --git a/lib/node_modules/@stdlib/namespace/aliases/package.json b/lib/node_modules/@stdlib/namespace/aliases/package.json index 615e4ff38a1e..7ce88feacd4b 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/package.json +++ b/lib/node_modules/@stdlib/namespace/aliases/package.json @@ -26,6 +26,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/package.json b/lib/node_modules/@stdlib/namespace/pkg2alias/package.json index 365f6a9438e3..ed6dc3a5ef23 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/package.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/package.json @@ -26,6 +26,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/package.json b/lib/node_modules/@stdlib/namespace/pkg2related/package.json index 6106eab4162c..f0194c259336 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/package.json +++ b/lib/node_modules/@stdlib/namespace/pkg2related/package.json @@ -26,6 +26,7 @@ "lib": "./lib", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { From 4321c6b4600e74a34355f5c486aaadc0324412cf Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 18:55:59 -0700 Subject: [PATCH 111/142] Rename CLI alias --- lib/node_modules/@stdlib/repl/help/README.md | 4 ++-- lib/node_modules/@stdlib/repl/help/docs/usage.txt | 2 +- lib/node_modules/@stdlib/repl/help/lib/index.js | 2 +- lib/node_modules/@stdlib/repl/help/package.json | 4 ++-- 4 files changed, 6 insertions(+), 6 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/help/README.md b/lib/node_modules/@stdlib/repl/help/README.md index 62158e8228c2..6c14451cec58 100644 --- a/lib/node_modules/@stdlib/repl/help/README.md +++ b/lib/node_modules/@stdlib/repl/help/README.md @@ -116,7 +116,7 @@ for ( i = 0; i < 100; i++ ) { ### Usage ```text -Usage: stdlib-help-text [options] +Usage: stdlib-alias-help [options] Options: @@ -143,7 +143,7 @@ Options: ### Examples ```bash -$ stdlib-help-text 'base.sin' +$ stdlib-alias-help 'base.sin' ``` diff --git a/lib/node_modules/@stdlib/repl/help/docs/usage.txt b/lib/node_modules/@stdlib/repl/help/docs/usage.txt index 8405d794390c..2b510bc0cad6 100644 --- a/lib/node_modules/@stdlib/repl/help/docs/usage.txt +++ b/lib/node_modules/@stdlib/repl/help/docs/usage.txt @@ -1,5 +1,5 @@ -Usage: stdlib-help-text [options] +Usage: stdlib-alias-help [options] Options: diff --git a/lib/node_modules/@stdlib/repl/help/lib/index.js b/lib/node_modules/@stdlib/repl/help/lib/index.js index 30d29a14bc3d..6b7afaa98c63 100644 --- a/lib/node_modules/@stdlib/repl/help/lib/index.js +++ b/lib/node_modules/@stdlib/repl/help/lib/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. diff --git a/lib/node_modules/@stdlib/repl/help/package.json b/lib/node_modules/@stdlib/repl/help/package.json index e767eb6335d2..a0d300c1717d 100644 --- a/lib/node_modules/@stdlib/repl/help/package.json +++ b/lib/node_modules/@stdlib/repl/help/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/repl/help", "version": "0.0.0", - "description": "REPL help texts.", + "description": "Return help text associated with a provided alias.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", @@ -14,7 +14,7 @@ } ], "bin": { - "stdlib-help-text": "./bin/cli" + "stdlib-alias-help": "./bin/cli" }, "main": "./lib", "directories": { From fccff03f2a2c25f009ca7b87069e8b2a52c6d4e7 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 18:58:38 -0700 Subject: [PATCH 112/142] Rename data package --- lib/node_modules/@stdlib/repl/help/datapackage.json | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/help/datapackage.json b/lib/node_modules/@stdlib/repl/help/datapackage.json index a352c9174628..0caa20f23d58 100644 --- a/lib/node_modules/@stdlib/repl/help/datapackage.json +++ b/lib/node_modules/@stdlib/repl/help/datapackage.json @@ -1,11 +1,11 @@ { - "name": "stdlib-help-text", + "name": "stdlib-alias-help", "version": "", "title": "Standard Library Aliases and Help Texts", "description": "A mapping between standard library aliases and help texts.", "resources": [ { - "name": "stdlib-help-text-json", + "name": "stdlib-alias-help-json", "title": "Standard Library Aliases and Help Texts", "description": "A mapping between standard library aliases and help texts.", "format": "json", @@ -15,7 +15,7 @@ "path": "./data/data.json" }, { - "name": "stdlib-help-text-csv", + "name": "stdlib-alias-help-csv", "title": "Standard Library Aliases and Help Texts", "description": "A mapping between standard library aliases and help texts.", "format": "csv", From 1d031608756237fba9aa5cc5ce5db2507dcba148 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 19:11:18 -0700 Subject: [PATCH 113/142] Fix variable bug --- lib/node_modules/@stdlib/repl/help/scripts/build.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/repl/help/scripts/build.js b/lib/node_modules/@stdlib/repl/help/scripts/build.js index 2dc1bec33159..5bfe70f87b26 100644 --- a/lib/node_modules/@stdlib/repl/help/scripts/build.js +++ b/lib/node_modules/@stdlib/repl/help/scripts/build.js @@ -207,7 +207,7 @@ function main() { keys = objectKeys( json ); csv = ''; for ( i = 0; i < keys.length; i++ ) { - tmp = replace( json[ tmp[i] ], /\r?\n/g, '\\n' ); + tmp = replace( json[ keys[i] ], /\r?\n/g, '\\n' ); tmp = replace( tmp, '"', '\\"' ); csv += keys[ i ] + ',"' + tmp + '"\n'; // Note: ensures trailing newline } From de5a18a394489b73eabcc65fab4ed81c3c5cbec2 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 19:23:20 -0700 Subject: [PATCH 114/142] Fix resolution of package aliases --- .../@stdlib/repl/help/data/data.csv | 2542 ++++++++--------- .../@stdlib/repl/help/data/data.json | 2 +- .../@stdlib/repl/help/scripts/build.js | 6 +- 3 files changed, 1275 insertions(+), 1275 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/help/data/data.csv b/lib/node_modules/@stdlib/repl/help/data/data.csv index c45470ca30de..c404355e0be8 100644 --- a/lib/node_modules/@stdlib/repl/help/data/data.csv +++ b/lib/node_modules/@stdlib/repl/help/data/data.csv @@ -1,122 +1,122 @@ -AFINN_96,"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some "words" are phrases; e.g., "cashing in", "cool stuff".\n - Words may contain apostrophes; e.g., "can't stand".\n - Words may contain dashes; e.g., "cover-up", "made-up".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. "A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs." In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n" -AFINN_111,"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., "n00b".\n - Some "words" are phrases; e.g., "cool stuff", "not good".\n - Words may contain apostrophes; e.g., "can't stand".\n - Words may contain diaeresis; e.g., "naïve".\n - Words may contain dashes; e.g., "self-deluded", "self-confident".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. "A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs." In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n" -alias2pkg,"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( '{{alias:@stdlib/math/base/special/sin}}' )\n '@stdlib/math/base/special/sin'\n\n" -alias2related,"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( '{{alias:@stdlib/math/base/special/sin}}' )\n [...]\n\n" -aliases,"\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n" -allocUnsafe,"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n" +AFINN_96,"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n" +AFINN_111,"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n" +alias2pkg,"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n" +alias2related,"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n" +aliases,"\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n" +allocUnsafe,"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n" anova1,"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n" -ANSCOMBES_QUARTET,"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. "Graphs in Statistical Analysis." *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n" -any,"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n" -anyBy,"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n" -anyByAsync,"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n" -anyByRight,"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n" -anyByRightAsync,"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n" +ANSCOMBES_QUARTET,"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n" +any,"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n" +anyBy,"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n" +anyByAsync,"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n" +anyByRight,"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n" +anyByRightAsync,"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n" APERY,"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n" -append,"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n" -ARCH,"\nARCH\n Operating system CPU architecture.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n" -argumentFunction,"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n" -ARGV,"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n" -array,"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow "safe" casts.\n - 'same-kind': allow "safe" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n" -array2buffer,"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n" -array2iterator,"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n" -array2iteratorRight,"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n" -ArrayBuffer,"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n" -arraybuffer2buffer,"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new {{alias:@stdlib/array/buffer}}( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n" -arrayCtors,"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n" -arrayDataType,"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n" -arrayDataTypes,"\narrayDataTypes()\n Returns a list of array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n \n\n" -arrayMinDataType,"\narrayMinDataType( value )\n Returns the minimum array data type of the closest "kind" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n" -arrayNextDataType,"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n" -arrayPromotionRules,"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest "kind" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Array data type.\n\n dtype2: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n" -arraySafeCasts,"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n" -arraySameKindCasts,"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same "kind".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same "kind".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n" -arrayShape,"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n" -arrayStream,"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an "objectMode" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -arrayview2iterator,"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n" -arrayview2iteratorRight,"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n" -AsyncIteratorSymbol,"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n" -bartlettTest,"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups })\n\n" -base.abs,"\nbase.abs( x )\n Computes the absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n" -base.abs2,"\nbase.abs2( x )\n Computes the squared absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n" -base.absdiff,"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( {{alias:@stdlib/constants/math/float64-pinf}}, {{alias:@stdlib/constants/math/float64-ninf}} )\n Infinity\n > d = base.absdiff( {{alias:@stdlib/constants/math/float64-pinf}}, {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n\n" -base.absInt32,"\nbase.absInt32( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.absInt32( -1|0 )\n 1\n > v = base.absInt32( 2|0 )\n 2\n > v = base.absInt32( 0|0 )\n 0\n\n" -base.acos,"\nbase.acos( x )\n Compute the arccosine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n" -base.acosh,"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n" -base.acoth,"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent (in radians).\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n" -base.acovercos,"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n" -base.acoversin,"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n" -base.ahavercos,"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n" -base.ahaversin,"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n" -base.asin,"\nbase.asin( x )\n Computes the arcsine of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.0\n > y = base.asin( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n" -base.asinh,"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( {{alias:@stdlib/constants/math/float64-ninf}} )\n -Infinity\n > y = base.asinh( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n\n" -base.atan,"\nbase.atan( x )\n Computes the arctangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -{{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~-1.004\n > y = base.atan( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n" -base.atan2,"\nbase.atan2( y, x )\n Evaluates the arctangent of the quotient of two numbers.\n\n Parameters\n ----------\n y: number\n Numerator.\n\n x: number\n Denominator.\n\n Returns\n -------\n out: number\n Arctangent of `y/x` (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n" -base.atanh,"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n" -base.avercos,"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n" -base.aversin,"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n" +append,"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n" +ARCH,"\nARCH\n Operating system CPU architecture.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n" +argumentFunction,"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n" +ARGV,"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n" +array,"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n" +array2buffer,"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n" +array2iterator,"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n" +array2iteratorRight,"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n" +ArrayBuffer,"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n" +arraybuffer2buffer,"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n" +arrayCtors,"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n" +arrayDataType,"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n" +arrayDataTypes,"\narrayDataTypes()\n Returns a list of array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n \n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n" +arrayMinDataType,"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n" +arrayNextDataType,"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n" +arrayPromotionRules,"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Array data type.\n\n dtype2: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n" +arraySafeCasts,"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySameKindCasts, ndarraySafeCasts\n" +arraySameKindCasts,"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n" +arrayShape,"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n" +arrayStream,"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n" +arrayview2iterator,"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n" +arrayview2iteratorRight,"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n" +AsyncIteratorSymbol,"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n" +bartlettTest,"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups })\n\n See Also\n --------\n vartest\n" +base.abs,"\nbase.abs( x )\n Computes the absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2\n" +base.abs2,"\nbase.abs2( x )\n Computes the squared absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs\n" +base.absdiff,"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n" +base.absInt32,"\nbase.absInt32( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.absInt32( -1|0 )\n 1\n > v = base.absInt32( 2|0 )\n 2\n > v = base.absInt32( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n" +base.acos,"\nbase.acos( x )\n Compute the arccosine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n" +base.acosh,"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n" +base.acoth,"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent (in radians).\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atanh\n" +base.acovercos,"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n" +base.acoversin,"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n" +base.ahavercos,"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n" +base.ahaversin,"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n" +base.asin,"\nbase.asin( x )\n Computes the arcsine of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( PI/2.0 )\n ~1.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n" +base.asinh,"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n" +base.atan,"\nbase.atan( x )\n Computes the arctangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n" +base.atan2,"\nbase.atan2( y, x )\n Evaluates the arctangent of the quotient of two numbers.\n\n Parameters\n ----------\n y: number\n Numerator.\n\n x: number\n Denominator.\n\n Returns\n -------\n out: number\n Arctangent of `y/x` (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n" +base.atanh,"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n" +base.avercos,"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n" +base.aversin,"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n" base.bernoulli,"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.0\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n" -base.besselj0,"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.besselj0( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n" -base.besselj1,"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.besselj1( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n" -base.bessely0,"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.bessely0( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n" -base.bessely1,"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.bessely1( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n" -base.beta,"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n" -base.betainc,"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n" -base.betaincinv,"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n" -base.betaln,"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n" -base.binet,"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n" +base.besselj0,"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n" +base.besselj1,"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n" +base.bessely0,"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n" +base.bessely1,"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n" +base.beta,"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n" +base.betainc,"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n" +base.betaincinv,"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n" +base.betaln,"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n" +base.binet,"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n" base.binomcoef,"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n" base.binomcoefln,"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n" -base.boxcox,"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n" -base.boxcox1p,"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n" -base.boxcox1pinv,"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n" -base.boxcoxinv,"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n" -base.cabs,"\nbase.cabs( re, im )\n Computes the absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( 5.0, 3.0 )\n ~5.831\n\n" -base.cabs2,"\nbase.cabs2( re, im )\n Computes the squared absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( 5.0, 3.0 )\n 34.0\n\n" -base.cadd,"\nbase.cadd( [out,] re1, im1, re2, im2 )\n Adds two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cadd( 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float32}}( 2 );\n > y = base.cadd( out, 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n > var bool = ( y === out )\n true\n\n" -base.cbrt,"\nbase.cbrt( x )\n Computes the cube root.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n" -base.cceil,"\nbase.cceil( [out,] re, im )\n Rounds a complex number toward positive infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceil( 5.5, 3.3 )\n [ 6.0, 4.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cceil( out, 5.5, 3.3 )\n [ 6.0, 4.0 ]\n > var bool = ( v === out )\n true\n\n" -base.cceiln,"\nbase.cceiln( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward positive\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cceiln( out, 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n > var bool = ( v === out )\n true\n\n" -base.ccis,"\nbase.ccis( [out,] re, im )\n Computes the cis function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.ccis( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > var y = base.ccis( 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.ccis( out, 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n" -base.cdiv,"\nbase.cdiv( [out,] re1, im1, re2, im2 )\n Divides two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cdiv( -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cdiv( out, -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n" -base.ceil,"\nbase.ceil( x )\n Rounds a numeric value toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n" -base.ceil2,"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n" -base.ceil10,"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n" -base.ceilb,"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n" -base.ceiln,"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n" -base.ceilsd,"\nbase.ceilsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1 )\n 4.0\n > y = base.ceilsd( 12368.0, 2 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n" -base.cexp,"\nbase.cexp( [out,] re, im )\n Computes the exponential function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cexp( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > y = base.cexp( 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cexp( out, 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n" -base.cflipsign,"\nbase.cflipsign( [out,] re, im, y )\n Returns a complex number with the same magnitude as `z` and the sign of\n `y*z`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.cflipsign( -4.2, 5.5, -9 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cflipsign( out, -4.2, 5.5, 8 )\n [ -4.2, 5.5 ]\n > var bool = ( v === out )\n true\n\n" -base.cfloor,"\nbase.cfloor( [out,] re, im )\n Rounds a complex number toward negative infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cfloor( 5.5, 3.3 )\n [ 5.0, 3.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cfloor( out, 5.5, 3.3 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n" -base.cfloorn,"\nbase.cfloorn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward negative\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cfloorn( 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cfloorn( out, 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n > var bool = ( v === out )\n true\n\n" -base.cinv,"\nbase.cinv( [out,] re, im )\n Computes the inverse of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cinv( 2.0, 4.0 )\n [ 0.1, -0.2 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cinv( out, 2.0, 4.0 )\n [ 0.1, -0.2 ]\n > var bool = ( v === out )\n true\n\n" -base.clamp,"\nbase.clamp( v, min, max )\n Restricts a value to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n" -base.cmul,"\nbase.cmul( [out,] re1, im1, re2, im2 )\n Multiplies two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.cmul( 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cmul( out, 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n > var bool = ( v === out )\n true\n\n" -base.cneg,"\nbase.cneg( [out,] re, im )\n Negates a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Negated components.\n\n Examples\n --------\n > var out = base.cneg( -4.2, 5.5 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cneg( out, -4.2, 5.5 )\n [ 4.2, -5.5 ]\n > var bool = ( v === out )\n true\n\n" +base.boxcox,"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv" +base.boxcox1p,"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv" +base.boxcox1pinv,"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv" +base.boxcoxinv,"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv" +base.cabs,"\nbase.cabs( re, im )\n Computes the absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( 5.0, 3.0 )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n" +base.cabs2,"\nbase.cabs2( re, im )\n Computes the squared absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( 5.0, 3.0 )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n" +base.cadd,"\nbase.cadd( [out,] re1, im1, re2, im2 )\n Adds two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cadd( 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n\n // Provide an output array:\n > var out = new Float32Array( 2 );\n > y = base.cadd( out, 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n" +base.cbrt,"\nbase.cbrt( x )\n Computes the cube root.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n" +base.cceil,"\nbase.cceil( [out,] re, im )\n Rounds a complex number toward positive infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceil( 5.5, 3.3 )\n [ 6.0, 4.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cceil( out, 5.5, 3.3 )\n [ 6.0, 4.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n" +base.cceiln,"\nbase.cceiln( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward positive\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cceiln( out, 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n" +base.ccis,"\nbase.ccis( [out,] re, im )\n Computes the cis function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.ccis( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > var y = base.ccis( 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.ccis( out, 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n" +base.cdiv,"\nbase.cdiv( [out,] re1, im1, re2, im2 )\n Divides two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cdiv( -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.cdiv( out, -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cadd, base.cmul, base.csub\n" +base.ceil,"\nbase.ceil( x )\n Rounds a numeric value toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n" +base.ceil2,"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n" +base.ceil10,"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n" +base.ceilb,"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n" +base.ceiln,"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n" +base.ceilsd,"\nbase.ceilsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1 )\n 4.0\n > y = base.ceilsd( 12368.0, 2 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n" +base.cexp,"\nbase.cexp( [out,] re, im )\n Computes the exponential function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cexp( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > y = base.cexp( 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.cexp( out, 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n" +base.cflipsign,"\nbase.cflipsign( [out,] re, im, y )\n Returns a complex number with the same magnitude as `z` and the sign of\n `y*z`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.cflipsign( -4.2, 5.5, -9 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cflipsign( out, -4.2, 5.5, 8 )\n [ -4.2, 5.5 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cneg, base.csignum\n" +base.cfloor,"\nbase.cfloor( [out,] re, im )\n Rounds a complex number toward negative infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cfloor( 5.5, 3.3 )\n [ 5.0, 3.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cfloor( out, 5.5, 3.3 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n" +base.cfloorn,"\nbase.cfloorn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward negative\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cfloorn( 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cfloorn( out, 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n" +base.cinv,"\nbase.cinv( [out,] re, im )\n Computes the inverse of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cinv( 2.0, 4.0 )\n [ 0.1, -0.2 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.cinv( out, 2.0, 4.0 )\n [ 0.1, -0.2 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cdiv\n" +base.clamp,"\nbase.clamp( v, min, max )\n Restricts a value to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.wrap\n" +base.cmul,"\nbase.cmul( [out,] re1, im1, re2, im2 )\n Multiplies two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.cmul( 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n\n // Provide an output array:\n > var out = new Float64Array( 2 );\n > var v = base.cmul( out, 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n" +base.cneg,"\nbase.cneg( [out,] re, im )\n Negates a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Negated components.\n\n Examples\n --------\n > var out = base.cneg( -4.2, 5.5 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cneg( out, -4.2, 5.5 )\n [ 4.2, -5.5 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs\n" base.continuedFraction,"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 + a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n" -base.copysign,"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n" -base.cos,"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~0.707\n > y = base.cos( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n" -base.cosh,"\nbase.cosh( x )\n Computes the hyperbolic cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n" -base.cosm1,"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~-0.293\n > y = base.cosm1( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n" -base.cospi,"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n" -base.covercos,"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n" -base.coversin,"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n" -base.cphase,"\nbase.cphase( re, im )\n Computes the argument of a complex number in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( 5.0, 3.0 )\n ~0.5404\n\n" -base.cpolar,"\nbase.cpolar( [out,] re, im )\n Returns the absolute value and phase of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cpolar( out, 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n" -base.cround,"\nbase.cround( [out,] re, im )\n Rounds a complex number to the nearest integer.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cround( 5.5, 3.3 )\n [ 6.0, 3.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cround( out, 5.5, 3.3 )\n [ 6.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n" -base.croundn,"\nbase.croundn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.croundn( 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.croundn( out, 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n > var bool = ( v === out )\n true\n\n" -base.csignum,"\nbase.csignum( [out,] re, im )\n Evaluates the signum function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.csignum( -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.csignum( out, -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n > var bool = ( v === out )\n true\n\n" -base.csub,"\nbase.csub( [out,] re1, im1, re2, im2 )\n Subtracts two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.csub( 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.csub( out, 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n > var bool = ( v === out )\n true\n\n" -base.dasum,"\nbase.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.dasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.dasum( N, x1, stride )\n 12.0\n\n\nbase.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n\nbase.dasum.wasm( [options] )\n Returns a memory managed function to compute the sum of absolute values.\n\n For an externally defined `Float64Array`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.dasum.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var bytes = wasm.malloc( N * 8 );\n\n // Create a Float64Array view:\n > var view = new {{alias:@stdlib/array/float64}}( bytes.buffer, bytes.byteOffset, N );\n\n // Copy data to the heap:\n > view.set( [ 1.0, -2.0, 3.0, -4.0, 5.0 ] );\n\n // Compute the sum of absolute values (passing in the heap buffer):\n > var s = wasm( N, bytes, 1 )\n 15.0\n\n // Free the memory:\n > wasm.free( bytes );\n\n" -base.daxpy,"\nbase.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.daxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.daxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.daxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.wasm( [options] )\n Returns a memory managed function to multiply `x` by a constant `alpha` and\n add the result to `y`.\n\n For externally defined `Float64Arrays`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.daxpy.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var xbytes = wasm.malloc( N * 8 );\n > var ybytes = wasm.malloc( N * 8 );\n\n // Create Float64Array views:\n > var x = new {{alias:@stdlib/array/float64}}( xbytes.buffer, xbytes.byteOffset, N );\n > var y = new {{alias:@stdlib/array/float64}}( ybytes.buffer, ybytes.byteOffset, N );\n\n // Copy data to the heap:\n > x.set( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > y.set( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n\n // Multiply and add alpha:\n > var alpha = 5.0;\n > wasm( x.length, alpha, xbytes, 1, ybytes, 1 );\n > y\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Free the memory:\n > wasm.free( xbytes );\n > wasm.free( ybytes );\n\n" -base.dcopy,"\nbase.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.dcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.dcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.dcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n" -base.deg2rad,"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n" -base.digamma,"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n" -base.diracDelta,"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n" +base.copysign,"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n" +base.cos,"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n" +base.cosh,"\nbase.cosh( x )\n Computes the hyperbolic cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n" +base.cosm1,"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n" +base.cospi,"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n" +base.covercos,"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n" +base.coversin,"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n" +base.cphase,"\nbase.cphase( re, im )\n Computes the argument of a complex number in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( 5.0, 3.0 )\n ~0.5404\n\n See Also\n --------\n base.cabs\n" +base.cpolar,"\nbase.cpolar( [out,] re, im )\n Returns the absolute value and phase of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cpolar( out, 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase\n" +base.cround,"\nbase.cround( [out,] re, im )\n Rounds a complex number to the nearest integer.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cround( 5.5, 3.3 )\n [ 6.0, 3.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cround( out, 5.5, 3.3 )\n [ 6.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n" +base.croundn,"\nbase.croundn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.croundn( 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.croundn( out, 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n" +base.csignum,"\nbase.csignum( [out,] re, im )\n Evaluates the signum function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.csignum( -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.csignum( out, -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.signum\n" +base.csub,"\nbase.csub( [out,] re1, im1, re2, im2 )\n Subtracts two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.csub( 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.csub( out, 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n" +base.dasum,"\nbase.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > sum = base.dasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > sum = base.dasum( N, x1, stride )\n 12.0\n\n\nbase.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n\nbase.dasum.wasm( [options] )\n Returns a memory managed function to compute the sum of absolute values.\n\n For an externally defined `Float64Array`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.dasum.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var bytes = wasm.malloc( N * 8 );\n\n // Create a Float64Array view:\n > var view = new Float64Array( bytes.buffer, bytes.byteOffset, N );\n\n // Copy data to the heap:\n > view.set( [ 1.0, -2.0, 3.0, -4.0, 5.0 ] );\n\n // Compute the sum of absolute values (passing in the heap buffer):\n > var s = wasm( N, bytes, 1 )\n 15.0\n\n // Free the memory:\n > wasm.free( bytes );\n\n See Also\n --------\n base.daxpy, base.dcopy\n" +base.daxpy,"\nbase.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.daxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.daxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.daxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.wasm( [options] )\n Returns a memory managed function to multiply `x` by a constant `alpha` and\n add the result to `y`.\n\n For externally defined `Float64Arrays`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.daxpy.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var xbytes = wasm.malloc( N * 8 );\n > var ybytes = wasm.malloc( N * 8 );\n\n // Create Float64Array views:\n > var x = new Float64Array( xbytes.buffer, xbytes.byteOffset, N );\n > var y = new Float64Array( ybytes.buffer, ybytes.byteOffset, N );\n\n // Copy data to the heap:\n > x.set( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > y.set( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n\n // Multiply and add alpha:\n > var alpha = 5.0;\n > wasm( x.length, alpha, xbytes, 1, ybytes, 1 );\n > y\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Free the memory:\n > wasm.free( xbytes );\n > wasm.free( ybytes );\n\n See Also\n --------\n base.dasum, base.dcopy\n" +base.dcopy,"\nbase.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.dcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.dcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.dcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.dasum, base.daxpy\n" +base.deg2rad,"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n" +base.digamma,"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.trigamma, base.gamma\n" +base.diracDelta,"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n" base.dists.arcsine.Arcsine,"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n" -base.dists.arcsine.cdf,"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n" +base.dists.arcsine.cdf,"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n" base.dists.arcsine.entropy,"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n" base.dists.arcsine.kurtosis,"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n" -base.dists.arcsine.logcdf,"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n" +base.dists.arcsine.logcdf,"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n" base.dists.arcsine.logpdf,"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n" base.dists.arcsine.mean,"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n" base.dists.arcsine.median,"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n" @@ -242,10 +242,10 @@ base.dists.degenerate.pmf,"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates t base.dists.degenerate.quantile,"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n" base.dists.degenerate.stdev,"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n" base.dists.degenerate.variance,"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n" -base.dists.discreteUniform.cdf,"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n" +base.dists.discreteUniform.cdf,"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n" base.dists.discreteUniform.DiscreteUniform,"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n" base.dists.discreteUniform.kurtosis,"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n" -base.dists.discreteUniform.logcdf,"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n" +base.dists.discreteUniform.logcdf,"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n" base.dists.discreteUniform.logpmf,"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n" base.dists.discreteUniform.mean,"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n" base.dists.discreteUniform.median,"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n" @@ -255,7 +255,7 @@ base.dists.discreteUniform.quantile,"\nbase.dists.discreteUniform.quantile( p, a base.dists.discreteUniform.skewness,"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n" base.dists.discreteUniform.stdev,"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n" base.dists.discreteUniform.variance,"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n" -base.dists.erlang.cdf,"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n" +base.dists.erlang.cdf,"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n" base.dists.erlang.entropy,"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n" base.dists.erlang.Erlang,"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n" base.dists.erlang.kurtosis,"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n" @@ -282,7 +282,7 @@ base.dists.exponential.quantile,"\nbase.dists.exponential.quantile( p, λ )\n base.dists.exponential.skewness,"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n" base.dists.exponential.stdev,"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n" base.dists.exponential.variance,"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n" -base.dists.f.cdf,"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n" +base.dists.f.cdf,"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n" base.dists.f.entropy,"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of a F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n" base.dists.f.F,"\nbase.dists.f.F( [d1, d2] )\n Returns a F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n" base.dists.f.kurtosis,"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of a F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n" @@ -307,7 +307,7 @@ base.dists.frechet.quantile,"\nbase.dists.frechet.quantile( p, α, s, m )\n E base.dists.frechet.skewness,"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n" base.dists.frechet.stdev,"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n" base.dists.frechet.variance,"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n" -base.dists.gamma.cdf,"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n" +base.dists.gamma.cdf,"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n" base.dists.gamma.entropy,"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n" base.dists.gamma.Gamma,"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n" base.dists.gamma.kurtosis,"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n" @@ -361,7 +361,7 @@ base.dists.hypergeometric.quantile,"\nbase.dists.hypergeometric.quantile( p, N, base.dists.hypergeometric.skewness,"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n" base.dists.hypergeometric.stdev,"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n" base.dists.hypergeometric.variance,"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n" -base.dists.invgamma.cdf,"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n" +base.dists.invgamma.cdf,"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n" base.dists.invgamma.entropy,"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n" base.dists.invgamma.InvGamma,"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n" base.dists.invgamma.kurtosis,"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n" @@ -467,10 +467,10 @@ base.dists.normal.quantile,"\nbase.dists.normal.quantile( p, μ, σ )\n Evalu base.dists.normal.skewness,"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n" base.dists.normal.stdev,"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n" base.dists.normal.variance,"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n" -base.dists.pareto1.cdf,"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n" +base.dists.pareto1.cdf,"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n" base.dists.pareto1.entropy,"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n" base.dists.pareto1.kurtosis,"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n" -base.dists.pareto1.logcdf,"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n" +base.dists.pareto1.logcdf,"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n" base.dists.pareto1.logpdf,"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n" base.dists.pareto1.mean,"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n" base.dists.pareto1.median,"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n" @@ -535,10 +535,10 @@ base.dists.triangular.skewness,"\nbase.dists.triangular.skewness( a, b, c )\n base.dists.triangular.stdev,"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n" base.dists.triangular.Triangular,"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n" base.dists.triangular.variance,"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n" -base.dists.uniform.cdf,"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n" +base.dists.uniform.cdf,"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n" base.dists.uniform.entropy,"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n" base.dists.uniform.kurtosis,"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n" -base.dists.uniform.logcdf,"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n" +base.dists.uniform.logcdf,"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n" base.dists.uniform.logpdf,"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n" base.dists.uniform.mean,"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n" base.dists.uniform.median,"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n" @@ -549,10 +549,10 @@ base.dists.uniform.skewness,"\nbase.dists.uniform.skewness( a, b )\n Returns base.dists.uniform.stdev,"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n" base.dists.uniform.Uniform,"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n" base.dists.uniform.variance,"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n" -base.dists.weibull.cdf,"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n" +base.dists.weibull.cdf,"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n" base.dists.weibull.entropy,"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n" base.dists.weibull.kurtosis,"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n" -base.dists.weibull.logcdf,"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n" +base.dists.weibull.logcdf,"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n" base.dists.weibull.logpdf,"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n" base.dists.weibull.mean,"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n" base.dists.weibull.median,"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n" @@ -564,137 +564,137 @@ base.dists.weibull.skewness,"\nbase.dists.weibull.skewness( k, λ )\n Returns base.dists.weibull.stdev,"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n" base.dists.weibull.variance,"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n" base.dists.weibull.Weibull,"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n" -base.ellipe,"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n > y = base.ellipe( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n" -base.ellipk,"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n > y = base.ellipk( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n" -base.epsdiff,"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n" -base.erf,"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n" -base.erfc,"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.erfc( {{alias:@stdlib/constants/math/float64-ninf}} )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n" -base.erfcinv,"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n" -base.erfinv,"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n" +base.ellipe,"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipk\n" +base.ellipk,"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe\n" +base.epsdiff,"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n" +base.erf,"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n" +base.erfc,"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv\n" +base.erfcinv,"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv\n" +base.erfinv,"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n" base.eta,"\nbase.eta( s )\n Evaluates the Dirichlet eta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n" -base.evalpoly,"\nbase.evalpoly( c, x )\n Evaluates a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n" -base.evalrational,"\nbase.evalrational( P, Q, x )\n Evaluates a rational function.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n" -base.exp,"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n" -base.exp2,"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n" -base.exp10,"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n" -base.expit,"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n" -base.expm1,"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n" -base.expm1rel,"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n \n" -base.exponent,"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n" -base.exponentf,"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e34 ) )\n 114\n > exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n" -base.factorial,"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n" -base.factorialln,"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n" -base.fallingFactorial,"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n" -base.fibonacci,"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n" -base.fibonacciIndex,"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n" -base.fibpoly,"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n" -base.flipsign,"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`, else behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.14, 10.0 )\n -3.14\n > z = base.flipsign( -3.14, -1.0 )\n 3.14\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.14, -0.0 )\n 3.14\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n" -base.float32ToInt32,"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( 4294967295.0 ) )\n -1\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14 ) )\n 3\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n -3\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( NaN ) )\n 0\n > y = base.float32ToInt32( {{alias:@stdlib/constants/math/float32-pinf}} )\n 0\n > y = base.float32ToInt32( {{alias:@stdlib/constants/math/float32-ninf}} )\n 0\n" -base.float32ToUint32,"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( 4294967297.0 ) )\n 1\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14 ) )\n 3\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( NaN ) )\n 0\n > y = base.float32ToUint32( {{alias:@stdlib/constants/math/float32-pinf}} )\n 0\n > y = base.float32ToUint32( {{alias:@stdlib/constants/math/float32-ninf}} )\n 0\n" +base.evalpoly,"\nbase.evalpoly( c, x )\n Evaluates a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n" +base.evalrational,"\nbase.evalrational( P, Q, x )\n Evaluates a rational function.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n" +base.exp,"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n" +base.exp2,"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10\n" +base.exp10,"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2\n" +base.expit,"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit" +base.expm1,"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n" +base.expm1rel,"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n \n See Also\n --------\n base.exp, base.expm1\n" +base.exponent,"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n" +base.exponentf,"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n" +base.factorial,"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n" +base.factorialln,"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n" +base.fallingFactorial,"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n" +base.fibonacci,"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n" +base.fibonacciIndex,"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n" +base.fibpoly,"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n" +base.flipsign,"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`, else behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.14, 10.0 )\n -3.14\n > z = base.flipsign( -3.14, -1.0 )\n 3.14\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.14, -0.0 )\n 3.14\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n" +base.float32ToInt32,"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n -1\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32" +base.float32ToUint32,"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 1\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32" base.float64ToFloat32,"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n" -base.float64ToInt32,"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0\n > y = base.float64ToInt32( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0\n" -base.float64ToUint32,"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0\n > y = base.float64ToUint32( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0\n" -base.floor,"\nbase.floor( x )\n Rounds a numeric value toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n" -base.floor2,"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n" -base.floor10,"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n" -base.floorb,"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n" -base.floorn,"\nbase.floorn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward negative\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n" -base.floorsd,"\nbase.floorsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5 )\n 3.1415\n > y = base.floorsd( 3.14159, 1 )\n 3.0\n > y = base.floorsd( 12368.0, 2 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n" -base.fresnel,"\nbase.fresnel( [out,] x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.fresnel( out, 0.0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n" -base.fresnelc,"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( {{alias:@stdlib/constants/math/float64-pinf}} )\n ~0.5\n > y = base.fresnelc( {{alias:@stdlib/constants/math/float64-ninf}} )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n" -base.fresnels,"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( {{alias:@stdlib/constants/math/float64-pinf}} )\n ~0.5\n > y = base.fresnels( {{alias:@stdlib/constants/math/float64-ninf}} )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n" -base.frexp,"\nbase.frexp( [out,] x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, 0 ]\n > out = base.frexp( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var y = base.frexp( out, 4.0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n" -base.fromBinaryString,"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n" -base.fromBinaryStringf,"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n" -base.fromBinaryStringUint8,"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n" -base.fromBinaryStringUint16,"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n" -base.fromBinaryStringUint32,"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n" -base.fromWordf,"\nbase.fromWordf( x )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n" -base.fromWords,"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n" -base.gamma,"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n" -base.gamma1pm1,"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n" -base.gammaDeltaRatio,"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n" -base.gammainc,"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n" -base.gammaincinv,"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n" -base.gammaLanczosSum,"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n" -base.gammaLanczosSumExpGScaled,"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n" -base.gammaln,"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n" -base.gasum,"\nbase.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.gasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.gasum( N, x1, stride )\n 12.0\n\n\nbase.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > sum = base.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n" -base.gaxpy,"\nbase.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gaxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.gaxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gaxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n" -base.gcd,"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n" -base.gcopy,"\nbase.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.gcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n" -base.getHighWord,"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n" -base.getLowWord,"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n" -base.hacovercos,"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n" -base.hacoversin,"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n" -base.havercos,"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n" -base.haversin,"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n" -base.heaviside,"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n" -base.hermitepoly,"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n" +base.float64ToInt32,"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32" +base.float64ToUint32,"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32" +base.floor,"\nbase.floor( x )\n Rounds a numeric value toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n" +base.floor2,"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n" +base.floor10,"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n" +base.floorb,"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n" +base.floorn,"\nbase.floorn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward negative\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n" +base.floorsd,"\nbase.floorsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5 )\n 3.1415\n > y = base.floorsd( 3.14159, 1 )\n 3.0\n > y = base.floorsd( 12368.0, 2 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n" +base.fresnel,"\nbase.fresnel( [out,] x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n > var out = new Float64Array( 2 );\n > var v = base.fresnel( out, 0.0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels\n" +base.fresnelc,"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n" +base.fresnels,"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n" +base.frexp,"\nbase.frexp( [out,] x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var y = base.frexp( out, 4.0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n" +base.fromBinaryString,"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n" +base.fromBinaryStringf,"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n" +base.fromBinaryStringUint8,"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n" +base.fromBinaryStringUint16,"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n" +base.fromBinaryStringUint32,"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n" +base.fromWordf,"\nbase.fromWordf( x )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n" +base.fromWords,"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n" +base.gamma,"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n" +base.gamma1pm1,"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n" +base.gammaDeltaRatio,"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n" +base.gammainc,"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n" +base.gammaincinv,"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n" +base.gammaLanczosSum,"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n" +base.gammaLanczosSumExpGScaled,"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n" +base.gammaln,"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n" +base.gasum,"\nbase.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > sum = base.gasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > sum = base.gasum( N, x1, stride )\n 12.0\n\n\nbase.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > sum = base.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.dasum, base.sasum\n" +base.gaxpy,"\nbase.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > base.gaxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.gaxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = base.floor( x.length / 2 );\n > base.gaxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.daxpy, base.saxpy\n" +base.gcd,"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n" +base.gcopy,"\nbase.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = base.floor( x.length / 2 );\n > base.gcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.gcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = base.floor( x.length / 2 );\n > base.gcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.dcopy\n" +base.getHighWord,"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n" +base.getLowWord,"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n" +base.hacovercos,"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n" +base.hacoversin,"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n" +base.havercos,"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n" +base.haversin,"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n" +base.heaviside,"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n" +base.hermitepoly,"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n" base.hypot,"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n" -base.imul,"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n" -base.imuldw,"\nbase.imuldw( [out,] a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n" -base.int32ToUint32,"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( {{alias:@stdlib/number/float64/base/to-int32}}( -32 ) )\n 4294967264\n > y = base.int32ToUint32( {{alias:@stdlib/number/float64/base/to-int32}}( 3 ) )\n 3\n\n" -base.inv,"\nbase.inv( x )\n Computes the multiplicative inverse of `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n" -base.isEven,"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n" -base.isEvenInt32,"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n" -base.isFinite,"\nbase.isFinite( x )\n Tests if a numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( {{alias:@stdlib/constants/math/float64-pinf}} )\n false\n > bool = base.isFinite( {{alias:@stdlib/constants/math/float64-ninf}} )\n false\n\n" -base.isInfinite,"\nbase.isInfinite( x )\n Tests if a numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( {{alias:@stdlib/constants/math/float64-pinf}} )\n true\n > bool = base.isInfinite( {{alias:@stdlib/constants/math/float64-ninf}} )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n" +base.imul,"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw, base.uimul\n" +base.imuldw,"\nbase.imuldw( [out,] a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n See Also\n --------\n base.imul, base.uimuldw\n" +base.int32ToUint32,"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n" +base.inv,"\nbase.inv( x )\n Computes the multiplicative inverse of `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n" +base.isEven,"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n" +base.isEvenInt32,"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n" +base.isFinite,"\nbase.isFinite( x )\n Tests if a numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n" +base.isInfinite,"\nbase.isInfinite( x )\n Tests if a numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n" base.isInteger,"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n" base.isnan,"\nbase.isnan( x )\n Tests if a numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n" -base.isNegativeInteger,"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n" -base.isNegativeZero,"\nbase.isNegativeZero( x )\n Tests if a numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n" -base.isNonNegativeInteger,"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n" -base.isNonPositiveInteger,"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n" -base.isOdd,"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n" -base.isOddInt32,"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n" -base.isPositiveInteger,"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n" -base.isPositiveZero,"\nbase.isPositiveZero( x )\n Tests if a numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n" +base.isNegativeInteger,"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n" +base.isNegativeZero,"\nbase.isNegativeZero( x )\n Tests if a numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n" +base.isNonNegativeInteger,"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n" +base.isNonPositiveInteger,"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n" +base.isOdd,"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n" +base.isOddInt32,"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n" +base.isPositiveInteger,"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n" +base.isPositiveZero,"\nbase.isPositiveZero( x )\n Tests if a numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n" base.isPow2Uint32,"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n" base.isProbability,"\nbase.isProbability( x )\n Tests if a numeric value is a probability.\n\n A probability is defined as a numeric value on the closed interval `[0,1]`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n" -base.isSafeInteger,"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is "safe" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n" -base.kernelBetainc,"\nbase.kernelBetainc( [out,] x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.32, 1.6 ]\n\n > out = new Array( 2 );\n > var v = base.kernelBetainc( out, 0.2, 1.0, 2.0, true, true )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n" -base.kernelBetaincinv,"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n" -base.kernelCos,"\nbase.kernelCos( x, y )\n Computes the cosine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n" -base.kernelSin,"\nbase.kernelSin( x, y )\n Computes the sine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n" -base.kernelTan,"\nbase.kernelTan( x, y, k )\n Computes the tangent of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n" -base.kroneckerDelta,"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n" -base.lcm,"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n" -base.ldexp,"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( {{alias:@stdlib/constants/math/float64-pinf}}, 11 )\n Infinity\n > x = base.ldexp( {{alias:@stdlib/constants/math/float64-ninf}}, -118 )\n -Infinity\n\n" -base.ln,"\nbase.ln( x )\n Evaluates the natural logarithm.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n" -base.log,"\nbase.log( x, b )\n Computes the base `b` logarithm of `x`.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n" -base.log1mexp,"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n" -base.log1p,"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n" -base.log1pexp,"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n" -base.log2,"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n" -base.log10,"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n" -base.logaddexp,"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n" +base.isSafeInteger,"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n" +base.kernelBetainc,"\nbase.kernelBetainc( [out,] x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.32, 1.6 ]\n\n > out = new Array( 2 );\n > var v = base.kernelBetainc( out, 0.2, 1.0, 2.0, true, true )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n" +base.kernelBetaincinv,"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n" +base.kernelCos,"\nbase.kernelCos( x, y )\n Computes the cosine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n" +base.kernelSin,"\nbase.kernelSin( x, y )\n Computes the sine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n" +base.kernelTan,"\nbase.kernelTan( x, y, k )\n Computes the tangent of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n" +base.kroneckerDelta,"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n" +base.lcm,"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n" +base.ldexp,"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n" +base.ln,"\nbase.ln( x )\n Evaluates the natural logarithm.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n" +base.log,"\nbase.log( x, b )\n Computes the base `b` logarithm of `x`.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n" +base.log1mexp,"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp" +base.log1p,"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n" +base.log1pexp,"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p" +base.log2,"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n" +base.log10,"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n" +base.logaddexp,"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n" base.logit,"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n" -base.lucas,"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n" -base.lucaspoly,"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n" -base.max,"\nbase.max( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n" -base.maxabs,"\nbase.maxabs( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n" -base.min,"\nbase.min( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n" -base.minabs,"\nbase.minabs( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n" -base.minmax,"\nbase.minmax( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmax( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmax( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n" -base.minmaxabs,"\nbase.minmaxabs( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabs( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmaxabs( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n" -base.modf,"\nbase.modf( [out,] x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n parts: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, +0.0 ]\n > parts = base.modf( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > parts = base.modf( out, 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n\n" -base.ndarray,"\nbase.ndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarray( 'float64', 3 )\n \n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n" -base.ndarrayMemoized,"\nbase.ndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarrayMemoized( 'float64', 3 )\n \n > var f = base.ndarrayMemoized( 'float64', 3 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n" -base.negafibonacci,"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n" -base.negalucas,"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n" -base.nonfibonacci,"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n" -base.normalize,"\nbase.normalize( [out,] x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*{{alias:@stdlib/math/base/special/pow}}(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, 0 ]\n > out = base.normalize( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.normalize( out, 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > bool = ( v === out )\n true\n\n" -base.normalizef,"\nbase.normalizef( [out,] x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( {{alias:@stdlib/number/float64/base/to-float32}}( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*{{alias:@stdlib/math/base/special/pow}}(2,exp) === {{alias:@stdlib/number/float64/base/to-float32}}(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( {{alias:@stdlib/constants/math/float32-pinf}} )\n [ Infinity, 0 ]\n > out = base.normalizef( {{alias:@stdlib/constants/math/float32-ninf}} )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float32}}( 2 );\n > var v = base.normalizef( out, {{alias:@stdlib/number/float64/base/to-float32}}( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n" -base.normhermitepoly,"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n" +base.lucas,"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n" +base.lucaspoly,"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n" +base.max,"\nbase.max( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n" +base.maxabs,"\nbase.maxabs( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n" +base.min,"\nbase.min( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs\n" +base.minabs,"\nbase.minabs( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n" +base.minmax,"\nbase.minmax( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmax( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmax( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs\n" +base.minmaxabs,"\nbase.minmaxabs( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabs( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmaxabs( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n" +base.modf,"\nbase.modf( [out,] x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n parts: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new Float64Array( 2 );\n > parts = base.modf( out, 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n\n" +base.ndarray,"\nbase.ndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarray( 'float64', 3 )\n \n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n See Also\n --------\n array, ndarray\n" +base.ndarrayMemoized,"\nbase.ndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarrayMemoized( 'float64', 3 )\n \n > var f = base.ndarrayMemoized( 'float64', 3 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n See Also\n --------\n array, base.ndarray, ndarray, ndarrayMemoized\n" +base.negafibonacci,"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n" +base.negalucas,"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n" +base.nonfibonacci,"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n" +base.normalize,"\nbase.normalize( [out,] x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.normalize( out, 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n" +base.normalizef,"\nbase.normalizef( [out,] x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new Float32Array( 2 );\n > var v = base.normalizef( out, base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize\n" +base.normhermitepoly,"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n" base.pdiff,"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n" -base.polygamma,"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n" -base.pow,"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( {{alias:@stdlib/constants/math/float64-pi}}, 5.0 )\n ~306.0197\n > y = base.pow( {{alias:@stdlib/constants/math/float64-pi}}, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n" -base.powm1,"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( {{alias:@stdlib/constants/math/float64-pi}}, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n" -base.rad2deg,"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n 90.0\n > d = base.rad2deg( -{{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( {{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n 29.999999999999996\n\n" -base.ramp,"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n" -base.random.arcsine,"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" -base.random.bernoulli,"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.polygamma,"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n" +base.pow,"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n" +base.powm1,"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n" +base.rad2deg,"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n" +base.ramp,"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n" +base.random.arcsine,"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.beta\n" +base.random.bernoulli,"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.binomial\n" base.random.beta,"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" base.random.betaprime,"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" base.random.binomial,"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" @@ -719,272 +719,272 @@ base.random.laplace,"\nbase.random.laplace( μ, b )\n Returns a pseudorandom base.random.levy,"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" base.random.logistic,"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" base.random.lognormal,"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" -base.random.minstd,"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the "randomness quality" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" -base.random.minstdShuffle,"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the "randomness\n quality" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" -base.random.mt19937,"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[1, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 1\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.minstd,"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstdShuffle, base.random.mt19937, base.random.randi\n" +base.random.minstdShuffle,"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstd, base.random.mt19937, base.random.randi\n" +base.random.mt19937,"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[1, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 1\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstd, base.random.randi\n" base.random.negativeBinomial,"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" base.random.normal,"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" base.random.pareto1,"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" base.random.poisson,"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" -base.random.randi,"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" -base.random.randn,"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" -base.random.randu,"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.randi,"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n" +base.random.randn,"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.improvedZiggurat, base.random.randu\n" +base.random.randu,"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.discreteUniform, base.random.randn\n" base.random.rayleigh,"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" base.random.t,"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function\n returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" base.random.triangular,"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" -base.random.uniform,"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" +base.random.uniform,"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.discreteUniform, base.random.randu\n" base.random.weibull,"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n" -base.reldiff,"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = {{alias:@stdlib/math/base/special/abs}}( x );\n ... y = {{alias:@stdlib/math/base/special/abs}}( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * {{alias:@stdlib/constants/math/float64-eps}};\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n" +base.reldiff,"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n" base.rempio2,"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = new Array( 2 );\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n" -base.risingFactorial,"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n" -base.rotl32,"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( y )\n '00000000000000000000011000000000'\n\n" -base.rotr32,"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( y )\n '00000000010000000000000000000000'\n\n" -base.round,"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n" -base.round2,"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n" -base.round10,"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n" -base.roundb,"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n" -base.roundn,"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n" -base.roundsd,"\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n" -base.rsqrt,"\nbase.rsqrt( x )\n Computes the reciprocal square root.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n" -base.sasum,"\nbase.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.sasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.sasum( N, x1, stride )\n 12.0\n\n\nbase.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n" -base.saxpy,"\nbase.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.saxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.saxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.saxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n" -base.scopy,"\nbase.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.scopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.scopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.scopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n" -base.setHighWord,"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( {{alias:@stdlib/constants/math/float64-pinf}}, high )\n 1.0\n\n" -base.setLowWord,"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( {{alias:@stdlib/constants/math/float64-pinf}}, low )\n NaN\n > y = base.setLowWord( {{alias:@stdlib/constants/math/float64-ninf}}, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n" -base.sici,"\nbase.sici( [out,] x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > y = base.sici( out, 3.0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n\n" -base.signbit,"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n" -base.signbitf,"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( {{alias:@stdlib/number/float64/base/to-float32}}( 4.0 ) )\n false\n > bool = base.signbitf( {{alias:@stdlib/number/float64/base/to-float32}}( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n" -base.significandf,"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e34 ) )\n 4293751\n > s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e-34 ) )\n 5288021\n > s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n" +base.risingFactorial,"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n" +base.rotl32,"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n" +base.rotr32,"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n" +base.round,"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n" +base.round2,"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n" +base.round10,"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n" +base.roundb,"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n" +base.roundn,"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n" +base.roundsd,"\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n" +base.rsqrt,"\nbase.rsqrt( x )\n Computes the reciprocal square root.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n" +base.sasum,"\nbase.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > sum = base.sasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > sum = base.sasum( N, x1, stride )\n 12.0\n\n\nbase.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.dasum\n" +base.saxpy,"\nbase.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > base.saxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.saxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.saxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.daxpy\n" +base.scopy,"\nbase.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.scopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.scopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.scopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.dcopy\n" +base.setHighWord,"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n" +base.setLowWord,"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n" +base.sici,"\nbase.sici( [out,] x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new Float64Array( 2 );\n > y = base.sici( out, 3.0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n\n" +base.signbit,"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n" +base.signbitf,"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n" +base.significandf,"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n" base.signum,"\nbase.signum( x )\n Evaluates the signum function.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n" -base.sin,"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.0\n > y = base.sin( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n" -base.sinc,"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n" -base.sincos,"\nbase.sincos( [out,] x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.sincos( out, 0.0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n" -base.sincospi,"\nbase.sincospi( [out,] x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.sincospi( out, 0.0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n" -base.sinh,"\nbase.sinh( x )\n Computes the hyperbolic sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n" -base.sinpi,"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n" +base.sin,"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n" +base.sinc,"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n" +base.sincos,"\nbase.sincos( [out,] x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n > var out = new Float64Array( 2 );\n > var v = base.sincos( out, 0.0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi\n" +base.sincospi,"\nbase.sincospi( [out,] x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n > var out = new Float64Array( 2 );\n > var v = base.sincospi( out, 0.0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi\n" +base.sinh,"\nbase.sinh( x )\n Computes the hyperbolic sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n" +base.sinpi,"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n" base.spence,"\nbase.spence( x )\n Evaluates Spence’s function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n" -base.sqrt,"\nbase.sqrt( x )\n Computes the principal square root.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n" -base.sqrt1pm1,"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n" +base.sqrt,"\nbase.sqrt( x )\n Computes the principal square root.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n" +base.sqrt1pm1,"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n" base.sumSeries,"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n" -base.tan,"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -{{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~-1.0\n > y = base.tan( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n" -base.tanh,"\nbase.tanh( x )\n Computes the hyperbolic tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n" -base.toBinaryString,"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-pi}} )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-pinf}} )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-ninf}} )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n" -base.toBinaryStringf,"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( {{alias:@stdlib/constants/math/float64-pi}} ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/constants/math/float32-pinf}} )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/constants/math/float32-ninf}} )\n '11111111100000000000000000000000'\n\n" -base.toBinaryStringUint8,"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint8}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n" -base.toBinaryStringUint16,"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint16}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n" -base.toBinaryStringUint32,"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint32}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n" -base.toWordf,"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = {{alias:@stdlib/number/float64/base/to-float32}}( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n" -base.toWords,"\nbase.toWords( [out,] x )\n Splits a floating-point number into a higher order word (unsigned 32-bit\n integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/uint32}}( 2 );\n > w = base.toWords( out, 3.14e201 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n" -base.trigamma,"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n" -base.trunc,"\nbase.trunc( x )\n Rounds a numeric value toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n" -base.trunc2,"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n" -base.trunc10,"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n" -base.truncb,"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n" -base.truncn,"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n" -base.truncsd,"\nbase.truncsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5 )\n 3.1415\n > y = base.truncsd( 3.14159, 1 )\n 3.0\n > y = base.truncsd( 12368.0, 2 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n" -base.uimul,"\nbase.uimul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.uimul( 10>>>0, 4>>>0 )\n 40\n\n" -base.uimuldw,"\nbase.uimuldw( [out,] a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.uimuldw( 1, 10 )\n [ 0, 10 ]\n\n" -base.uint32ToInt32,"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( {{alias:@stdlib/number/float64/base/to-uint32}}( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( {{alias:@stdlib/number/float64/base/to-uint32}}( 3 ) )\n 3\n\n" -base.vercos,"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n" -base.versin,"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n" -base.wrap,"\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n" -base.xlog1py,"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n" -base.xlogy,"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n" +base.tan,"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n" +base.tanh,"\nbase.tanh( x )\n Computes the hyperbolic tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n" +base.toBinaryString,"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n" +base.toBinaryStringf,"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n" +base.toBinaryStringUint8,"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n" +base.toBinaryStringUint16,"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n" +base.toBinaryStringUint32,"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n" +base.toWordf,"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n" +base.toWords,"\nbase.toWords( [out,] x )\n Splits a floating-point number into a higher order word (unsigned 32-bit\n integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n // Provide an output array:\n > var out = new Uint32Array( 2 );\n > w = base.toWords( out, 3.14e201 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf" +base.trigamma,"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n" +base.trunc,"\nbase.trunc( x )\n Rounds a numeric value toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n" +base.trunc2,"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n" +base.trunc10,"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n" +base.truncb,"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n" +base.truncn,"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n" +base.truncsd,"\nbase.truncsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5 )\n 3.1415\n > y = base.truncsd( 3.14159, 1 )\n 3.0\n > y = base.truncsd( 12368.0, 2 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n" +base.uimul,"\nbase.uimul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.uimul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n" +base.uimuldw,"\nbase.uimuldw( [out,] a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.uimuldw( 1, 10 )\n [ 0, 10 ]\n\n See Also\n --------\n base.imuldw, base.uimul\n" +base.uint32ToInt32,"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n" +base.vercos,"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n" +base.versin,"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n" +base.wrap,"\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n" +base.xlog1py,"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n" +base.xlogy,"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n" base.zeta,"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n" BERNDT_CPS_WAGES_1985,"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n" -bifurcate,"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n" -bifurcateBy,"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n" -bifurcateByAsync,"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n" -bifurcateIn,"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n" -bifurcateOwn,"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n" +bifurcate,"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n" +bifurcateBy,"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n" +bifurcateByAsync,"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n" +bifurcateIn,"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n" +bifurcateOwn,"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n" binomialTest,"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n" -Buffer,"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n" -buffer2json,"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n The returned JSON object has the following properties:\n\n - type: value type\n - data: buffer data as a generic array\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/buffer/alloc-unsafe}}( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n" -capitalize,"\ncapitalize( str )\n Capitalizes the first character in a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n" -capitalizeKeys,"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n" +Buffer,"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n" +buffer2json,"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n The returned JSON object has the following properties:\n\n - type: value type\n - data: buffer data as a generic array\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n" +capitalize,"\ncapitalize( str )\n Capitalizes the first character in a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n" +capitalizeKeys,"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n" CATALAN,"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n" -CBRT_EPS,"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n" -chdir,"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n" -chi2gof,"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can be expected frequencies, population probabilities\n summing to one, or a discrete probability distribution name to test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: Array\n Observation frequencies.\n\n y: Array|string\n Expected frequencies (or probabilities) or a discrete probability\n distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p )\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.print()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.print()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts )\n {...}\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = {{alias:@stdlib/random/base/poisson}}.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new {{alias:@stdlib/array/int32}}( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda )\n {...}\n\n" -circarray2iterator,"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n" -circularArrayStream,"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an "objectMode" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -CircularBuffer,"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n buf.clear: Function\n Clears the buffer.\n\n buf.count: integer\n Number of elements currently in the buffer.\n\n buf.full: boolean\n Boolean indicating whether the buffer is full.\n\n buf.iterator: Function\n Returns an iterator for iterating over a buffer. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that a\n returned iterator does **not** iterate over partially full buffers.\n\n buf.length: integer\n Buffer length (capacity).\n\n buf.push: Function\n Adds a value to the buffer. If the buffer is full, the method returns\n the removed value; otherwise, the method returns `undefined`.\n\n buf.toArray: Function\n Returns an array of buffer values.\n\n buf.toJSON: Function\n Serializes a circular buffer as JSON.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n" +CBRT_EPS,"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n" +chdir,"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n" +chi2gof,"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can be expected frequencies, population probabilities\n summing to one, or a discrete probability distribution name to test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: Array\n Observation frequencies.\n\n y: Array|string\n Expected frequencies (or probabilities) or a discrete probability\n distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p )\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.print()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.print()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts )\n {...}\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda )\n {...}\n\n" +circarray2iterator,"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n" +circularArrayStream,"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n" +CircularBuffer,"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n buf.clear: Function\n Clears the buffer.\n\n buf.count: integer\n Number of elements currently in the buffer.\n\n buf.full: boolean\n Boolean indicating whether the buffer is full.\n\n buf.iterator: Function\n Returns an iterator for iterating over a buffer. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that a\n returned iterator does **not** iterate over partially full buffers.\n\n buf.length: integer\n Buffer length (capacity).\n\n buf.push: Function\n Adds a value to the buffer. If the buffer is full, the method returns\n the removed value; otherwise, the method returns `undefined`.\n\n buf.toArray: Function\n Returns an array of buffer values.\n\n buf.toJSON: Function\n Serializes a circular buffer as JSON.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n See Also\n --------\n FIFO, Stack\n" CMUDICT,"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary\n - phones: manners of articulation for each sound\n - symbols: complete list of ARPABET symbols used by the dictionary\n - vp: verbal pronunciations of punctuation marks\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n" -complex,"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n" -Complex64,"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 4.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 8.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n" -COMPLEX64_NUM_BYTES,"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n" -Complex128,"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 8.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 16.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n" -COMPLEX128_NUM_BYTES,"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n" -compose,"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n" -composeAsync,"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n" -configdir,"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n" -conj,"\nconj( z )\n Returns the complex conjugate of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Complex\n Complex conjugate.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n" -constantFunction,"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n" -constantStream,"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an "objectMode" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -constructorName,"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n" +complex,"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n" +Complex64,"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 4.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 8.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n See Also\n --------\n complex, Complex128\n" +COMPLEX64_NUM_BYTES,"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n" +Complex128,"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 8.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 16.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n See Also\n --------\n complex, Complex64\n" +COMPLEX128_NUM_BYTES,"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n" +compose,"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n" +composeAsync,"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n" +configdir,"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n" +conj,"\nconj( z )\n Returns the complex conjugate of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Complex\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n" +constantFunction,"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n" +constantStream,"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n" +constructorName,"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n" contains,"\ncontains( val, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `val` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `val` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does not distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n val: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n" -convertArray,"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n The function supports the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n arr: Array|TypedArray\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n" -convertArraySame,"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n The function supports input arrays having the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n x: Array|TypedArray\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new {{alias:@stdlib/array/float32}}( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n" +convertArray,"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n The function supports the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n arr: Array|TypedArray\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n" +convertArraySame,"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n The function supports input arrays having the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n x: Array|TypedArray\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n" convertPath,"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\foo\\bar\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\foo\\bar\\beep.c', 'win32' )\n 'C:\\\\foo\\bar\\beep.c'\n > out = convertPath( 'C:\\\\foo\\bar\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\foo\\bar\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n" -copy,"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n" -copyBuffer,"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = {{alias:@stdlib/buffer/from-array}}( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n" -countBy,"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n" -countByAsync,"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { "even": 2, "odd": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { "even": 2, "odd": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { "even": 2, "odd": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { "even": 2, "odd": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { "even": 2, "odd": 2 }\n\n" -curry,"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n" -curryRight,"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n" -cwd,"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n" +copy,"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n" +copyBuffer,"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n" +countBy,"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n" +countByAsync,"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n" +curry,"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n" +curryRight,"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n" +cwd,"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n" DALE_CHALL_NEW,"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n\n Returns\n -------\n out: Array\n List of familiar English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n" datasets,"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n" -dayOfQuarter,"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n" -dayOfYear,"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n" -daysInMonth,"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n" -daysInYear,"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n" -debugSinkStream,"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an "objectMode" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in "objectMode".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n" -debugStream,"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an "objectMode" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in "objectMode".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n" -deepEqual,"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: bool\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n" -deepGet,"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n" -deepHasOwnProp,"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for "own" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for "own" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n" -deepHasProp,"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n" -deepPluck,"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n" -deepSet,"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n" -defineMemoizedProperty,"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n" -defineProperties,"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n" -defineProperty,"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n" -dirname,"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n" -DoublyLinkedList,"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n "snapshot", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n" -doUntil,"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n" -doUntilAsync,"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n" -doUntilEach,"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n" -doUntilEachRight,"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n" -doWhile,"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n" -doWhileAsync,"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n" -doWhileEach,"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n" -doWhileEachRight,"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n" +dayOfQuarter,"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n" +dayOfYear,"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n" +daysInMonth,"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n" +daysInYear,"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n" +debugSinkStream,"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n" +debugStream,"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n" +deepEqual,"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: bool\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n" +deepGet,"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n" +deepHasOwnProp,"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n" +deepHasProp,"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n" +deepPluck,"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n" +deepSet,"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n" +defineMemoizedProperty,"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n" +defineProperties,"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n" +defineProperty,"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n" +dirname,"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n" +DoublyLinkedList,"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n" +doUntil,"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n" +doUntilAsync,"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n" +doUntilEach,"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n" +doUntilEachRight,"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n" +doWhile,"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n" +doWhileAsync,"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n" +doWhileEach,"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n" +doWhileEachRight,"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n" E,"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n" -emptyStream,"\nemptyStream( [options] )\n Returns an "empty" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an "objectMode" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -endsWith,"\nendsWith( str, search[, len] )\n Tests if a `string` ends with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` ends with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n" -enumerableProperties,"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n" -enumerablePropertiesIn,"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n" -enumerablePropertySymbols,"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n" -enumerablePropertySymbolsIn,"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n" -ENV,"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n" -EPS,"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n" -error2json,"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n" +emptyStream,"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n" +endsWith,"\nendsWith( str, search[, len] )\n Tests if a `string` ends with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` ends with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n" +enumerableProperties,"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n" +enumerablePropertiesIn,"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n" +enumerablePropertySymbols,"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n" +enumerablePropertySymbolsIn,"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n" +ENV,"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n" +EPS,"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n" +error2json,"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n" EULERGAMMA,"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n" -every,"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n" -everyBy,"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n" -everyByAsync,"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n" -everyByRight,"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n" -everyByRightAsync,"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n" -evil,"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `"use strict";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n" -exists,"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n" +every,"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n" +everyBy,"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n" +everyByAsync,"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n" +everyByRight,"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n" +everyByRightAsync,"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n" +evil,"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n" +exists,"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n" expandContractions,"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\'t be able to get y\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\'t to be my fault, because, you know, I didn\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n" -extname,"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n" -fastmath.abs,"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n" -fastmath.acosh,"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n" -fastmath.ampbm,"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n" -fastmath.asinh,"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n" -fastmath.atanh,"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n" -fastmath.hypot,"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n" -fastmath.log2Uint32,"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n" -fastmath.max,"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n" -fastmath.min,"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n" -fastmath.powint,"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n" -fastmath.sqrtUint32,"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n" -FEMALE_FIRST_NAMES_EN,"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. "Moby Word II." .\n\n" -FIFO,"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the "oldest" queue value (i.e., the value which is "first-out").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n "snapshot", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the "newest" queue value (i.e., the value which is "last-out").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current "first-out" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n" +extname,"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n" +fastmath.abs,"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n" +fastmath.acosh,"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n" +fastmath.ampbm,"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n" +fastmath.asinh,"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n" +fastmath.atanh,"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n" +fastmath.hypot,"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n" +fastmath.log2Uint32,"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n" +fastmath.max,"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n" +fastmath.min,"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n" +fastmath.powint,"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n" +fastmath.sqrtUint32,"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n" +FEMALE_FIRST_NAMES_EN,"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n" +FIFO,"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n" find,"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n" -flattenArray,"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: Array\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n" -flattenObject,"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n" -flignerTest,"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups })\n\n" -FLOAT16_CBRT_EPS,"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n" -FLOAT16_EPS,"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n" -FLOAT16_EXPONENT_BIAS,"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n" -FLOAT16_MAX,"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n" -FLOAT16_MAX_SAFE_INTEGER,"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n" -FLOAT16_MIN_SAFE_INTEGER,"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n" -FLOAT16_NINF,"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n" -FLOAT16_NUM_BYTES,"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n" -FLOAT16_PINF,"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n" -FLOAT16_PRECISION,"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n" -FLOAT16_SMALLEST_NORMAL,"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n" -FLOAT16_SMALLEST_SUBNORMAL,"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n" -FLOAT16_SQRT_EPS,"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n" -FLOAT32_CBRT_EPS,"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566601151848\n\n" -FLOAT32_EPS,"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n" -FLOAT32_EXPONENT_BIAS,"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n" -FLOAT32_MAX,"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n" -FLOAT32_MAX_SAFE_INTEGER,"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n" -FLOAT32_MIN_SAFE_INTEGER,"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n" -FLOAT32_NINF,"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n" -FLOAT32_NUM_BYTES,"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n" -FLOAT32_PINF,"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n" -FLOAT32_PRECISION,"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n" -FLOAT32_SMALLEST_NORMAL,"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n" -FLOAT32_SMALLEST_SUBNORMAL,"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n" -FLOAT32_SQRT_EPS,"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n" -Float32Array,"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/float64}}( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n" -FLOAT64_EXPONENT_BIAS,"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n" -FLOAT64_HIGH_WORD_EXPONENT_MASK,"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > {{alias:@stdlib/number/uint32/base/to-binary-string}}( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n" -FLOAT64_HIGH_WORD_SIGNIFICAND_MASK,"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > {{alias:@stdlib/number/uint32/base/to-binary-string}}( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n" -FLOAT64_MAX,"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n" -FLOAT64_MAX_BASE2_EXPONENT,"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n" -FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL,"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n" -FLOAT64_MAX_BASE10_EXPONENT,"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n" -FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL,"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n" -FLOAT64_MAX_LN,"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n" -FLOAT64_MAX_SAFE_FIBONACCI,"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n" -FLOAT64_MAX_SAFE_INTEGER,"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n" -FLOAT64_MAX_SAFE_LUCAS,"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n" -FLOAT64_MAX_SAFE_NTH_FIBONACCI,"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n" -FLOAT64_MAX_SAFE_NTH_LUCAS,"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n" -FLOAT64_MIN_BASE2_EXPONENT,"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n" -FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL,"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n" -FLOAT64_MIN_BASE10_EXPONENT,"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n" -FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL,"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n" -FLOAT64_MIN_LN,"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n" -FLOAT64_MIN_SAFE_INTEGER,"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n" -FLOAT64_NUM_BYTES,"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n" -FLOAT64_PRECISION,"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n" -FLOAT64_SMALLEST_NORMAL,"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n" -FLOAT64_SMALLEST_SUBNORMAL,"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n" -Float64Array,"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/float32}}( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n" -forEach,"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n" -forEachAsync,"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n" -forEachRight,"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n" -forEachRightAsync,"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n" -forIn,"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n" -forOwn,"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n" -FOURTH_PI,"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n" -FOURTH_ROOT_EPS,"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n" -FRB_SF_WAGE_RIGIDITY,"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. "Wage Rigidity." .\n\n" +flattenArray,"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: Array\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n" +flattenObject,"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n" +flignerTest,"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups })\n\n See Also\n --------\n bartlettTest\n" +FLOAT16_CBRT_EPS,"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n" +FLOAT16_EPS,"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n" +FLOAT16_EXPONENT_BIAS,"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n" +FLOAT16_MAX,"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n" +FLOAT16_MAX_SAFE_INTEGER,"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n" +FLOAT16_MIN_SAFE_INTEGER,"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n" +FLOAT16_NINF,"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n" +FLOAT16_NUM_BYTES,"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n" +FLOAT16_PINF,"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n" +FLOAT16_PRECISION,"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n" +FLOAT16_SMALLEST_NORMAL,"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n" +FLOAT16_SMALLEST_SUBNORMAL,"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n" +FLOAT16_SQRT_EPS,"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n" +FLOAT32_CBRT_EPS,"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566601151848\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n" +FLOAT32_EPS,"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n" +FLOAT32_EXPONENT_BIAS,"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n" +FLOAT32_MAX,"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n" +FLOAT32_MAX_SAFE_INTEGER,"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n" +FLOAT32_MIN_SAFE_INTEGER,"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n" +FLOAT32_NINF,"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n" +FLOAT32_NUM_BYTES,"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n" +FLOAT32_PINF,"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n" +FLOAT32_PRECISION,"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n" +FLOAT32_SMALLEST_NORMAL,"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n" +FLOAT32_SMALLEST_SUBNORMAL,"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n" +FLOAT32_SQRT_EPS,"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n" +Float32Array,"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n" +FLOAT64_EXPONENT_BIAS,"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n" +FLOAT64_HIGH_WORD_EXPONENT_MASK,"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n" +FLOAT64_HIGH_WORD_SIGNIFICAND_MASK,"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK\n" +FLOAT64_MAX,"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n" +FLOAT64_MAX_BASE2_EXPONENT,"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n" +FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL,"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n" +FLOAT64_MAX_BASE10_EXPONENT,"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n" +FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL,"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n" +FLOAT64_MAX_LN,"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n" +FLOAT64_MAX_SAFE_FIBONACCI,"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n" +FLOAT64_MAX_SAFE_INTEGER,"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n" +FLOAT64_MAX_SAFE_LUCAS,"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n" +FLOAT64_MAX_SAFE_NTH_FIBONACCI,"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n" +FLOAT64_MAX_SAFE_NTH_LUCAS,"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n" +FLOAT64_MIN_BASE2_EXPONENT,"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n" +FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL,"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n" +FLOAT64_MIN_BASE10_EXPONENT,"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n" +FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL,"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n" +FLOAT64_MIN_LN,"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n" +FLOAT64_MIN_SAFE_INTEGER,"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n" +FLOAT64_NUM_BYTES,"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n" +FLOAT64_PRECISION,"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n" +FLOAT64_SMALLEST_NORMAL,"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n" +FLOAT64_SMALLEST_SUBNORMAL,"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n" +Float64Array,"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n" +forEach,"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n" +forEachAsync,"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n" +forEachRight,"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n" +forEachRightAsync,"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n" +forIn,"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n" +forOwn,"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n" +FOURTH_PI,"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n" +FOURTH_ROOT_EPS,"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n" +FRB_SF_WAGE_RIGIDITY,"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n" fromCodePoint,"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n" -functionName,"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `"anonymous"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n" -functionSequence,"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n" -functionSequenceAsync,"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n" +functionName,"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n" +functionSequence,"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n" +functionSequenceAsync,"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n" GAMMA_LANCZOS_G,"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n" -getegid,"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n" -geteuid,"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n" -getgid,"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n" +getegid,"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n" +geteuid,"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n" +getgid,"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n" getGlobal,"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n" -getPrototypeOf,"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n" -getuid,"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n" +getPrototypeOf,"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n" +getuid,"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n" GLAISHER,"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n" -group,"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n" -groupBy,"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n" -groupByAsync,"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { "true": [ 1000, 3000 ], "false": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { "true": [ 2, 0 ], "false": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { "true": [ [ 2, 1000 ], [ 0, 3000 ] ], "false": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { "true": [ 3000, 1000 ], "false": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { "true": [ 3000, 1000 ], "false": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { "true": [ 3000, 1000 ], "false": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { "true": [ 2000, 1000 ], "false": [ 1500 ] }\n\n" -groupIn,"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n" -groupOwn,"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n" -HALF_LN2,"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n" -HALF_PI,"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n" -HARRISON_BOSTON_HOUSE_PRICES,"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. "Hedonic housing prices and\n the demand for clean air." _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. "On the Harrison and Rubinfeld\n Data." _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n" -HARRISON_BOSTON_HOUSE_PRICES_CORRECTED,"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. "Hedonic housing prices and\n the demand for clean air." _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. "On the Harrison and Rubinfeld\n Data." _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n" -hasArrayBufferSupport,"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n" +group,"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n" +groupBy,"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n" +groupByAsync,"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n" +groupIn,"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n" +groupOwn,"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n" +HALF_LN2,"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n" +HALF_PI,"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n" +HARRISON_BOSTON_HOUSE_PRICES,"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n" +HARRISON_BOSTON_HOUSE_PRICES_CORRECTED,"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n" +hasArrayBufferSupport,"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n" hasAsyncAwaitSupport,"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n" -hasAsyncIteratorSymbolSupport,"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n" +hasAsyncIteratorSymbolSupport,"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n" hasClassSupport,"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n" -hasDefinePropertiesSupport,"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n" -hasDefinePropertySupport,"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n" +hasDefinePropertiesSupport,"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n" +hasDefinePropertySupport,"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n" hasFloat32ArraySupport,"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n" hasFloat64ArraySupport,"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n" hasFunctionNameSupport,"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n" @@ -992,15 +992,15 @@ hasGeneratorSupport,"\nhasGeneratorSupport()\n Tests whether an environment s hasInt8ArraySupport,"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n" hasInt16ArraySupport,"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n" hasInt32ArraySupport,"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n" -hasIteratorSymbolSupport,"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n" +hasIteratorSymbolSupport,"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n" hasMapSupport,"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n" hasNodeBufferSupport,"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n" -hasOwnProp,"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n" -hasProp,"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n" +hasOwnProp,"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n" +hasProp,"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n" hasProxySupport,"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n" hasSetSupport,"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n" -hasSharedArrayBufferSupport,"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n" -hasSymbolSupport,"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n" +hasSharedArrayBufferSupport,"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n" +hasSymbolSupport,"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n" hasToStringTagSupport,"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n" hasUint8ArraySupport,"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n" hasUint8ClampedArraySupport,"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n" @@ -1009,496 +1009,496 @@ hasUint32ArraySupport,"\nhasUint32ArraySupport()\n Tests for native `Uint32Ar hasWeakMapSupport,"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n" hasWeakSetSupport,"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n" hasWebAssemblySupport,"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n" -HERNDON_VENUS_SEMIDIAMETERS,"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. "Sample Criteria for Testing Outlying\n Observations." _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. "Procedures for Detecting Outlying Observations in\n Samples." _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. "Some Grubbs-Type Statistics\n for the Detection of Several Outliers." _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n" -homedir,"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n" -HOURS_IN_DAY,"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n" -HOURS_IN_WEEK,"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n" -hoursInMonth,"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n" -hoursInYear,"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n" +HERNDON_VENUS_SEMIDIAMETERS,"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n" +homedir,"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n" +HOURS_IN_DAY,"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n" +HOURS_IN_WEEK,"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n" +hoursInMonth,"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n" +hoursInYear,"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n" httpServer,"\nhttpServer( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n createServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var createServer = httpServer()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > createServer = httpServer( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > createServer = httpServer( opts )\n \n\n\ncreateServer( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var createServer = httpServer();\n > createServer( done );\n\n" -identity,"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n" -ifelse,"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n" -ifelseAsync,"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object\n - result: either `x` or `y`\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n" -ifthen,"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n" -ifthenAsync,"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion\n\n The predicate function callback accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n" -imag,"\nimag( z )\n Returns the imaginary component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n" -IMG_ACANTHUS_MOLLIS,"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +identity,"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n" +ifelse,"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n" +ifelseAsync,"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object\n - result: either `x` or `y`\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n" +ifthen,"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n" +ifthenAsync,"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion\n\n The predicate function callback accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n" +imag,"\nimag( z )\n Returns the imaginary component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n" +IMG_ACANTHUS_MOLLIS,"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n" IMG_AIRPLANE_FROM_ABOVE,"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" -IMG_ALLIUM_OREOPHILUM,"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_ALLIUM_OREOPHILUM,"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n" IMG_BLACK_CANYON,"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" IMG_DUST_BOWL_HOME,"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" IMG_FRENCH_ALPINE_LANDSCAPE,"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" -IMG_LOCOMOTION_HOUSE_CAT,"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" -IMG_LOCOMOTION_NUDE_MALE,"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" +IMG_LOCOMOTION_HOUSE_CAT,"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n" +IMG_LOCOMOTION_NUDE_MALE,"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n" IMG_MARCH_PASTORAL,"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" IMG_NAGASAKI_BOATS,"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n" -incrapcorr,"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n" -incrcount,"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n" -incrcovariance,"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n" -incrcovmat,"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n" -incrcv,"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n" -increwmean,"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n" -increwstdev,"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n" -increwvariance,"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n" -incrgmean,"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n" -incrgrubbs,"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( {{alias:@stdlib/random/base/normal}}( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. "Sample Criteria for Testing Outlying\n Observations." _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. "Procedures for Detecting Outlying Observations in\n Samples." _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n" -incrhmean,"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n" -incrkmeans,"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n" -incrkurtosis,"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n" -incrmaape,"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n" -incrmae,"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n" -incrmapcorr,"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n" -incrmape,"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n" -incrmax,"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n" -incrmaxabs,"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n" -incrmcovariance,"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n" -incrmcv,"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n" -incrmda,"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n" -incrme,"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n" -incrmean,"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n" -incrmeanabs,"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n" -incrmeanabs2,"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n" -incrmeanstdev,"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n" -incrmeanvar,"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n" -incrmgmean,"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n" -incrmgrubbs,"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( {{alias:@stdlib/random/base/normal}}( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. "Sample Criteria for Testing Outlying\n Observations." _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. "Procedures for Detecting Outlying Observations in\n Samples." _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n" -incrmhmean,"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n" -incrmidrange,"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n" -incrmin,"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n" -incrminabs,"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n" -incrminmax,"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n" -incrminmaxabs,"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n" -incrmmaape,"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n" -incrmmae,"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n" -incrmmape,"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n" -incrmmax,"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n" -incrmmaxabs,"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n" -incrmmda,"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n" -incrmme,"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n" -incrmmean,"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n" -incrmmeanabs,"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n" -incrmmeanabs2,"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n" -incrmmeanstdev,"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n" -incrmmeanvar,"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n" -incrmmidrange,"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n" -incrmmin,"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n" -incrmminabs,"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n" -incrmminmax,"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n" -incrmminmaxabs,"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n" -incrmmpe,"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n" -incrmmse,"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n" -incrmpcorr,"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n" -incrmpcorr2,"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n" -incrmpcorrdist,"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n" -incrmpe,"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n" -incrmprod,"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n" -incrmrange,"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n" -incrmrmse,"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n" -incrmrss,"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n" -incrmse,"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n" -incrmstdev,"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n" -incrmsum,"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n" -incrmsumabs,"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n" -incrmsumabs2,"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n" -incrmsummary,"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n" -incrmsumprod,"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n" -incrmvariance,"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n" -incrmvmr,"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n" -incrpcorr,"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n" -incrpcorr2,"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n" -incrpcorrdist,"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n" -incrpcorrdistmat,"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n" -incrpcorrmat,"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n" -incrprod,"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n" -incrrange,"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n" -incrrmse,"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n" -incrrss,"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n" -incrskewness,"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n" -incrspace,"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n" -incrstdev,"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n" -incrsum,"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n" -incrsumabs,"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n" -incrsumabs2,"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n" -incrsummary,"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n" -incrsumprod,"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n" -incrvariance,"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n" -incrvmr,"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n" -incrwmean,"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value\n - w: weight\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n" -ind2sub,"\nind2sub( [out,] shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'wrap', the function wraps around\n a linear index exceeding array dimensions using modulo arithmetic. If\n equal to 'clamp', the function sets a linear index exceeding array\n dimensions to either `0` (minimum linear index) or the maximum linear\n index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n // Provide an output array:\n > var out = new Array( d.length );\n > s = ind2sub( out, d, 17 )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n" +incrapcorr,"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n" +incrcount,"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n" +incrcovariance,"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n" +incrcovmat,"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n" +incrcv,"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n" +increwmean,"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n" +increwstdev,"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n" +increwvariance,"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n" +incrgmean,"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n" +incrgrubbs,"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n" +incrhmean,"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n" +incrkmeans,"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n" +incrkurtosis,"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n" +incrmaape,"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n" +incrmae,"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n" +incrmapcorr,"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n" +incrmape,"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n" +incrmax,"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n" +incrmaxabs,"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n" +incrmcovariance,"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n" +incrmcv,"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n" +incrmda,"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n" +incrme,"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n" +incrmean,"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n" +incrmeanabs,"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n" +incrmeanabs2,"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n" +incrmeanstdev,"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n" +incrmeanvar,"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n" +incrmgmean,"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n" +incrmgrubbs,"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n" +incrmhmean,"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n" +incrmidrange,"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n" +incrmin,"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n" +incrminabs,"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n" +incrminmax,"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n" +incrminmaxabs,"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n" +incrmmaape,"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n" +incrmmae,"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n" +incrmmape,"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n" +incrmmax,"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n" +incrmmaxabs,"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n" +incrmmda,"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n" +incrmme,"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n" +incrmmean,"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n" +incrmmeanabs,"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n" +incrmmeanabs2,"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n" +incrmmeanstdev,"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n" +incrmmeanvar,"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n" +incrmmidrange,"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n" +incrmmin,"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n" +incrmminabs,"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n" +incrmminmax,"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n" +incrmminmaxabs,"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n" +incrmmpe,"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n" +incrmmse,"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n" +incrmpcorr,"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n" +incrmpcorr2,"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n" +incrmpcorrdist,"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n" +incrmpe,"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n" +incrmprod,"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n" +incrmrange,"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n" +incrmrmse,"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n" +incrmrss,"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n" +incrmse,"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n" +incrmstdev,"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n" +incrmsum,"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n" +incrmsumabs,"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n" +incrmsumabs2,"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n" +incrmsummary,"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n" +incrmsumprod,"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n" +incrmvariance,"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n" +incrmvmr,"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n" +incrpcorr,"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n" +incrpcorr2,"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n" +incrpcorrdist,"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n" +incrpcorrdistmat,"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n" +incrpcorrmat,"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n" +incrprod,"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n" +incrrange,"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n" +incrrmse,"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n" +incrrss,"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n" +incrskewness,"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n" +incrspace,"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n" +incrstdev,"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n" +incrsum,"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n" +incrsumabs,"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n" +incrsumabs2,"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n" +incrsummary,"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n" +incrsumprod,"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n" +incrvariance,"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n" +incrvmr,"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n" +incrwmean,"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value\n - w: weight\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n" +ind2sub,"\nind2sub( [out,] shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'wrap', the function wraps around\n a linear index exceeding array dimensions using modulo arithmetic. If\n equal to 'clamp', the function sets a linear index exceeding array\n dimensions to either `0` (minimum linear index) or the maximum linear\n index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n // Provide an output array:\n > var out = new Array( d.length );\n > s = ind2sub( out, d, 17 )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n" indexOf,"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n" inherit,"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n" -inheritedEnumerableProperties,"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n" -inheritedEnumerablePropertySymbols,"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n" -inheritedKeys,"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n" -inheritedNonEnumerableProperties,"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n" -inheritedNonEnumerablePropertyNames,"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n" -inheritedNonEnumerablePropertySymbols,"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n" -inheritedProperties,"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n" -inheritedPropertyDescriptor,"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n" -inheritedPropertyDescriptors,"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n" -inheritedPropertyNames,"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n" -inheritedPropertySymbols,"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n" -inheritedWritableProperties,"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n" -inheritedWritablePropertyNames,"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n" -inheritedWritablePropertySymbols,"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n" -inmap,"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n" -inmapAsync,"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n" -inmapRight,"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n" -inmapRightAsync,"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n" -inspectSinkStream,"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an "objectMode" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in "objectMode".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n" -inspectStream,"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an "objectMode" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in "objectMode".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n" -instanceOf,"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n" -INT8_MAX,"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n" -INT8_MIN,"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n" -INT8_NUM_BYTES,"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n" -Int8Array,"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" -INT16_MAX,"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n" -INT16_MIN,"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n" -INT16_NUM_BYTES,"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n" -Int16Array,"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" -INT32_MAX,"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n" -INT32_MIN,"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n" -INT32_NUM_BYTES,"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n" -Int32Array,"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int16}}( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" -IS_BIG_ENDIAN,"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n" +inheritedEnumerableProperties,"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n" +inheritedEnumerablePropertySymbols,"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n" +inheritedKeys,"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n" +inheritedNonEnumerableProperties,"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n" +inheritedNonEnumerablePropertyNames,"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n" +inheritedNonEnumerablePropertySymbols,"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n" +inheritedProperties,"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n" +inheritedPropertyDescriptor,"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n" +inheritedPropertyDescriptors,"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n" +inheritedPropertyNames,"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n" +inheritedPropertySymbols,"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n" +inheritedWritableProperties,"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n" +inheritedWritablePropertyNames,"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n" +inheritedWritablePropertySymbols,"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n" +inmap,"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight\n" +inmapAsync,"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n" +inmapRight,"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap\n" +inmapRightAsync,"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n" +inspectSinkStream,"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n" +inspectStream,"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n" +instanceOf,"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n" +INT8_MAX,"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n" +INT8_MIN,"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n" +INT8_NUM_BYTES,"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n" +Int8Array,"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n" +INT16_MAX,"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n" +INT16_MIN,"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n" +INT16_NUM_BYTES,"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n" +Int16Array,"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n" +INT32_MAX,"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n" +INT32_MIN,"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n" +INT32_NUM_BYTES,"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n" +Int32Array,"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n" +IS_BIG_ENDIAN,"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n" IS_BROWSER,"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n" IS_DARWIN,"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n" -IS_ELECTRON,"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n" -IS_ELECTRON_MAIN,"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n" -IS_ELECTRON_RENDERER,"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n" -IS_LITTLE_ENDIAN,"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n" +IS_ELECTRON,"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n" +IS_ELECTRON_MAIN,"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n" +IS_ELECTRON_RENDERER,"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n" +IS_LITTLE_ENDIAN,"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n" IS_NODE,"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n" IS_WEB_WORKER,"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n" IS_WINDOWS,"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n" -isAbsolutePath,"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\foo\\bar\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\foo\\bar\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\bar\\baz' )\n false\n\n" -isAccessorProperty,"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n" -isAccessorPropertyIn,"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n" -isAlphagram,"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n" -isAlphaNumeric,"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n" -isAnagram,"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n" +isAbsolutePath,"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\foo\\bar\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\foo\\bar\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\bar\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n" +isAccessorProperty,"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n" +isAccessorPropertyIn,"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n" +isAlphagram,"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n" +isAlphaNumeric,"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n" +isAnagram,"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n" isArguments,"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n" -isArray,"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n" +isArray,"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n" isArrayArray,"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n" -isArrayBuffer,"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new {{alias:@stdlib/array/buffer}}( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n" -isArrayLength,"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n" -isArrayLike,"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n" -isArrayLikeObject,"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n" -isASCII,"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( {{alias:@stdlib/string/from-code-point}}( 130 ) )\n false\n\n" -isBetween,"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n" -isBetweenArray,"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n" -isBinaryString,"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n" +isArrayBuffer,"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n" +isArrayLength,"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n" +isArrayLike,"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject\n" +isArrayLikeObject,"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike\n" +isASCII,"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n" +isBetween,"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n" +isBetweenArray,"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n" +isBinaryString,"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n" isBoolean,"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n" isBooleanArray,"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n" -isBoxedPrimitive,"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n" -isBuffer,"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new {{alias:@stdlib/buffer/ctor}}( 'beep' ) )\n true\n > bool = isBuffer( new {{alias:@stdlib/buffer/ctor}}( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n" -isCapitalized,"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n" -isCentrosymmetricMatrix,"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 2, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n" -isCircular,"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n" -isCircularArray,"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n" -isCircularPlainObject,"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n" -isCollection,"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n" -isComplex,"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplex( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n" -isComplex64,"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n" -isComplex64Array,"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new {{alias:@stdlib/array/complex64}}( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n" -isComplex128,"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n" -isComplex128Array,"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new {{alias:@stdlib/array/complex128}}( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n" -isComplexLike,"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n" -isComplexTypedArray,"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new {{alias:@stdlib/array/complex64}}( 10 ) )\n true\n\n" -isConfigurableProperty,"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n" -isConfigurablePropertyIn,"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n" -isDataProperty,"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n" -isDataPropertyIn,"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n" +isBoxedPrimitive,"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n" +isBuffer,"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n" +isCapitalized,"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n" +isCentrosymmetricMatrix,"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 2, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n" +isCircular,"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n" +isCircularArray,"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n" +isCircularPlainObject,"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n" +isCollection,"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike\n" +isComplex,"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n" +isComplex64,"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n" +isComplex64Array,"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n" +isComplex128,"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n" +isComplex128Array,"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n" +isComplexLike,"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n" +isComplexTypedArray,"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n" +isConfigurableProperty,"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n" +isConfigurablePropertyIn,"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n" +isDataProperty,"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n" +isDataPropertyIn,"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n" isDateObject,"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n" -isDigitString,"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n" +isDigitString,"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n" isEmailAddress,"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n" -isEmptyArray,"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n" -isEmptyObject,"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n" -isEmptyString,"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n" -isEnumerableProperty,"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n" -isEnumerablePropertyIn,"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n" +isEmptyArray,"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray\n" +isEmptyObject,"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n" +isEmptyString,"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n" +isEnumerableProperty,"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n" +isEnumerablePropertyIn,"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n" isError,"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n" -isEvalError,"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n" -isEven,"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n" -isFalsy,"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n" -isFalsyArray,"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n" -isFinite,"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n" -isFiniteArray,"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n" -isFloat32Array,"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new {{alias:@stdlib/array/float32}}( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n" -isFloat64Array,"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new {{alias:@stdlib/array/float64}}( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n" +isEvalError,"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n" +isEven,"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n" +isFalsy,"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n" +isFalsyArray,"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n" +isFinite,"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n" +isFiniteArray,"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n" +isFloat32Array,"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n" +isFloat64Array,"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n" isFunction,"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n" -isFunctionArray,"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n" -isGeneratorObject,"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n" -isGeneratorObjectLike,"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n" -isHexString,"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n" -isInfinite,"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n" -isInheritedProperty,"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n" -isInt8Array,"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n" -isInt16Array,"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new {{alias:@stdlib/array/int16}}( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n" -isInt32Array,"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new {{alias:@stdlib/array/int32}}( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n" -isInteger,"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n" -isIntegerArray,"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n" -isIterableLike,"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n" -isIteratorLike,"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n" -isJSON,"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{"a":5}' )\n true\n > bool = isJSON( '{a":5}' )\n false\n\n" +isFunctionArray,"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n" +isGeneratorObject,"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n" +isGeneratorObjectLike,"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n" +isHexString,"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n" +isInfinite,"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n" +isInheritedProperty,"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n" +isInt8Array,"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n" +isInt16Array,"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n" +isInt32Array,"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n" +isInteger,"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n" +isIntegerArray,"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n" +isIterableLike,"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n" +isIteratorLike,"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n" +isJSON,"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n" isLeapYear,"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n" -isLowercase,"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n" -isMatrixLike,"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n" -isMethod,"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n" -isMethodIn,"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n" -isNamedTypedTupleLike,"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = {{alias:@stdlib/utils/named-typed-tuple}}( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n" -isnan,"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n" -isNaNArray,"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n" -isNativeFunction,"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n" -isndarrayLike,"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n" -isNegativeInteger,"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n" -isNegativeIntegerArray,"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n" -isNegativeNumber,"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n" -isNegativeNumberArray,"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n" -isNegativeZero,"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n" +isLowercase,"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n" +isMatrixLike,"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n" +isMethod,"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n" +isMethodIn,"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n" +isNamedTypedTupleLike,"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n" +isnan,"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n" +isNaNArray,"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n" +isNativeFunction,"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n" +isndarrayLike,"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n" +isNegativeInteger,"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n" +isNegativeIntegerArray,"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n" +isNegativeNumber,"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n" +isNegativeNumberArray,"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n" +isNegativeZero,"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n" isNodeBuiltin,"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n" -isNodeDuplexStreamLike,"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n" -isNodeReadableStreamLike,"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n" +isNodeDuplexStreamLike,"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n" +isNodeReadableStreamLike,"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n" isNodeREPL,"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n" isNodeStreamLike,"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n" -isNodeTransformStreamLike,"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n" -isNodeWritableStreamLike,"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n" -isNonConfigurableProperty,"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n" -isNonConfigurablePropertyIn,"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n" -isNonEnumerableProperty,"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n" -isNonEnumerablePropertyIn,"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n" -isNonNegativeInteger,"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n" -isNonNegativeIntegerArray,"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n" -isNonNegativeNumber,"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n" -isNonNegativeNumberArray,"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n" -isNonPositiveInteger,"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n" -isNonPositiveIntegerArray,"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n" -isNonPositiveNumber,"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n" -isNonPositiveNumberArray,"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n" -isNonSymmetricMatrix,"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n" -isNull,"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n" -isNullArray,"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n" +isNodeTransformStreamLike,"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n" +isNodeWritableStreamLike,"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n" +isNonConfigurableProperty,"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n" +isNonConfigurablePropertyIn,"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n" +isNonEnumerableProperty,"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n" +isNonEnumerablePropertyIn,"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n" +isNonNegativeInteger,"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n" +isNonNegativeIntegerArray,"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n" +isNonNegativeNumber,"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n" +isNonNegativeNumberArray,"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n" +isNonPositiveInteger,"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n" +isNonPositiveIntegerArray,"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n" +isNonPositiveNumber,"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n" +isNonPositiveNumberArray,"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n" +isNonSymmetricMatrix,"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n" +isNull,"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n" +isNullArray,"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n" isNumber,"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n" -isNumberArray,"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n" -isNumericArray,"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n\n" -isObject,"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n" -isObjectArray,"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n" -isObjectLike,"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n" -isOdd,"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n" +isNumberArray,"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n" +isNumericArray,"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n" +isObject,"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n" +isObjectArray,"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n" +isObjectLike,"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n" +isOdd,"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n" isoWeeksInYear,"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n" -isPersymmetricMatrix,"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n" -isPlainObject,"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n" -isPlainObjectArray,"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n" -isPositiveInteger,"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n" -isPositiveIntegerArray,"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n" -isPositiveNumber,"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n" -isPositiveNumberArray,"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n" -isPositiveZero,"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n" -isPrimitive,"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n" -isPrimitiveArray,"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n" -isPRNGLike,"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( {{alias:@stdlib/random/base/randu}} )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n" -isProbability,"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n" -isProbabilityArray,"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n" -isPrototypeOf,"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > {{alias:@stdlib/utils/inherit}}( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n" -isRangeError,"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n" -isReadableProperty,"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n" -isReadablePropertyIn,"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n" -isReadOnlyProperty,"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n" -isReadOnlyPropertyIn,"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n" -isReadWriteProperty,"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n" -isReadWritePropertyIn,"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n" -isReferenceError,"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n" +isPersymmetricMatrix,"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n" +isPlainObject,"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n" +isPlainObjectArray,"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n" +isPositiveInteger,"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n" +isPositiveIntegerArray,"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n" +isPositiveNumber,"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n" +isPositiveNumberArray,"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n" +isPositiveZero,"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n" +isPrimitive,"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n" +isPrimitiveArray,"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n" +isPRNGLike,"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n" +isProbability,"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n" +isProbabilityArray,"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n" +isPrototypeOf,"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n" +isRangeError,"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n" +isReadableProperty,"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n" +isReadablePropertyIn,"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n" +isReadOnlyProperty,"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n" +isReadOnlyPropertyIn,"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n" +isReadWriteProperty,"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n" +isReadWritePropertyIn,"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n" +isReferenceError,"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n" isRegExp,"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n" -isRegExpString,"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n" -isRelativePath,"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\bar\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\bar\\baz' )\n true\n > bool = isRelativePath( 'C:\\foo\\..\\bar\\baz' )\n false\n\n" -isSafeInteger,"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is "safe" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n" -isSafeIntegerArray,"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is "safe" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n" -isSameValue,"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n" -isSameValueZero,"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n" -isSharedArrayBuffer,"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new {{alias:@stdlib/array/shared-buffer}}( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n" -isSkewCentrosymmetricMatrix,"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 2, 1, -1, -2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n" -isSkewPersymmetricMatrix,"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 0, 0, -1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n" -isSkewSymmetricMatrix,"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, -1, 1, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n" -isSquareMatrix,"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, 0, 0, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n" -isStrictEqual,"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n" +isRegExpString,"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n" +isRelativePath,"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\bar\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\bar\\baz' )\n true\n > bool = isRelativePath( 'C:\\foo\\..\\bar\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n" +isSafeInteger,"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n" +isSafeIntegerArray,"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n" +isSameValue,"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n" +isSameValueZero,"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n" +isSharedArrayBuffer,"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n" +isSkewCentrosymmetricMatrix,"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 2, 1, -1, -2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n" +isSkewPersymmetricMatrix,"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 1, 0, 0, -1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n" +isSkewSymmetricMatrix,"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 0, -1, 1, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n" +isSquareMatrix,"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 0, 0, 0, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n" +isStrictEqual,"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n" isString,"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n" -isStringArray,"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n" +isStringArray,"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n" isSymbol,"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n" -isSymbolArray,"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n" -isSymmetricMatrix,"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n" -isSyntaxError,"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n" -isTruthy,"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n" -isTruthyArray,"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n" -isTypedArray,"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n\n" -isTypedArrayLength,"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n" -isTypedArrayLike,"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new {{alias:@stdlib/array/int16}}() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n" -isTypeError,"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n" -isUint8Array,"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new {{alias:@stdlib/array/uint8}}( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n" -isUint8ClampedArray,"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new {{alias:@stdlib/array/uint8c}}( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n" -isUint16Array,"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new {{alias:@stdlib/array/uint16}}( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n" -isUint32Array,"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new {{alias:@stdlib/array/uint32}}( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n" +isSymbolArray,"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n" +isSymmetricMatrix,"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 0, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n" +isSyntaxError,"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n" +isTruthy,"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n" +isTruthyArray,"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n" +isTypedArray,"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n" +isTypedArrayLength,"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n" +isTypedArrayLike,"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n" +isTypeError,"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n" +isUint8Array,"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n" +isUint8ClampedArray,"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n" +isUint16Array,"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n" +isUint32Array,"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n" isUNCPath,"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\server\\share\\foo\\bar\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n" -isUndefined,"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n" -isUndefinedOrNull,"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n" -isUnityProbabilityArray,"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new {{alias:@stdlib/array/uint8}}( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n" -isUppercase,"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n" +isUndefined,"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n" +isUndefinedOrNull,"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n" +isUnityProbabilityArray,"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n" +isUppercase,"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n" isURI,"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n" -isURIError,"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n" -isVectorLike,"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n" -isWhitespace,"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space ("WSpace=Y","WS") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property "WSpace=Y" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n" -isWritableProperty,"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n" -isWritablePropertyIn,"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n" -isWriteOnlyProperty,"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n" -isWriteOnlyPropertyIn,"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n" -iterAdd,"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n" -iterAdvance,"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n" -iterAny,"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n" -iterAnyBy,"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n" -iterator2array,"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value\n - index: iterated value index (zero-based)\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( {{alias:@stdlib/random/iter/randu}}( opts ) )\n\n" -iterator2arrayview,"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = {{alias:@stdlib/random/iter/randu}}({ 'iter': 10 });\n > var out = new {{alias:@stdlib/array/float64}}( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n" -iterator2arrayviewRight,"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = {{alias:@stdlib/random/iter/randu}}({ 'iter': 10 });\n > var out = new {{alias:@stdlib/array/float64}}( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n" -iteratorStream,"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = {{alias:@stdlib/random/iter/randu}}( opts );\n > var s = iteratorStream( it );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an "objectMode" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = {{alias:@stdlib/random/iter/randu}}( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -IteratorSymbol,"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n" -iterawgn,"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterawln,"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterawun,"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterBartlettHannPulse,"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterBartlettPulse,"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterConcat,"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n" -iterConstant,"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n" -iterCosineWave,"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterCounter,"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( {{alias:@stdlib/random/iter/randu}}() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n" -itercugmean,"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n" -itercuhmean,"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n" -itercumax,"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n" -itercumaxabs,"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n" -itercumean,"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n" -itercumeanabs,"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n" -itercumeanabs2,"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n" -itercumidrange,"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n" -itercumin,"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n" -itercuminabs,"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n" -itercuprod,"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n" -itercurange,"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n" -itercusum,"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n" -itercusumabs,"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n" -itercusumabs2,"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n" -iterDedupe,"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n" -iterDedupeBy,"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value\n - sprev: previous source iterated value\n - dprev: previous downstream iterated value\n - index: source iteration index (zero-based)\n - acc: previous resolved value\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a "duplicate".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n" -iterDiracComb,"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n" -iterDivide,"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n" -iterEmpty,"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n" -iterEvery,"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n" -iterEveryBy,"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n" -iterFibonacci,"\niterFibonacci( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacci();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n" -iterFill,"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( {{alias:@stdlib/random/iter/randu}}(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n" -iterFilter,"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n" -iterFilterMap,"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n" -iterFirst,"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n" -iterFlatTopPulse,"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterFlow,"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it1 = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it1 = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n" -iterForEach,"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( {{alias:@stdlib/random/iter/randu}}(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -iterHannPulse,"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterHead,"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( {{alias:@stdlib/random/iter/randu}}(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -iterIntersection,"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value "uniqueness" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n" -iterIntersectionByHash,"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered "unique" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n" -iterLanczosPulse,"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterLast,"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n" -iterLength,"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n" -iterMap,"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( {{alias:@stdlib/random/iter/randu}}(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -iterMapN,"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values\n - index: iteration index (zero-based)\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n" -itermax,"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n" -itermaxabs,"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n" -itermean,"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n" -itermeanabs,"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n" -itermeanabs2,"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n" -itermidrange,"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n" -itermin,"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n" -iterminabs,"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n" -itermmax,"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n" -itermmaxabs,"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n" -itermmean,"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n" -itermmeanabs,"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n" -itermmeanabs2,"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n" -itermmidrange,"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n" -itermmin,"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n" -itermminabs,"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n" -iterMod,"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n" -itermprod,"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n" -itermrange,"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n" -itermsum,"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n" -itermsumabs,"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n" -itermsumabs2,"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n" -iterMultiply,"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n" -iterNone,"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n" -iterNoneBy,"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n" -iterNonFibonacci,"\niterNonFibonacci( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacci();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n" -iterNth,"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n" -iterPeriodicSinc,"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterPipeline,"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/iter/pipeline-thunk}}( {{alias:@stdlib/iter/head}}, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = {{alias:@stdlib/iter/pipeline-thunk}}( {{alias:@stdlib/iter/some-by}}, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( {{alias:@stdlib/random/iter/randu}}() )\n \n\n" -iterPop,"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n" -iterprod,"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n" -iterPulse,"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n" -iterPush,"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n" -iterrange,"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n" -iterReject,"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n" -iterReplicate,"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n" -iterReplicateBy,"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value\n - index: source iteration index (zero-based)\n - n: iteration index (zero-based)\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n" -iterSawtoothWave,"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterShift,"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n" -iterSineWave,"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterSlice,"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( {{alias:@stdlib/random/iter/randu}}(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -iterSome,"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n" -iterSomeBy,"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n" -iterSquareWave,"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n" -iterstdev,"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n" -iterSubtract,"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 5.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n" -itersum,"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n" -itersumabs,"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n" -itersumabs2,"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n" -iterThunk,"\niterThunk( iterFcn[, ...args] )\n Returns an iterator "thunk".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( {{alias:@stdlib/iter/some}}, 3 );\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n" -iterTriangleWave,"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n" -iterUnion,"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value "uniqueness" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n" -iterUnique,"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value "uniqueness" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n" -iterUniqueBy,"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered "unique" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n" -iterUniqueByHash,"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered "unique" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n" -iterUnshift,"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n" -itervariance,"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n" -joinStream,"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an "objectMode" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in "objectMode".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n" +isURIError,"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n" +isVectorLike,"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n" +isWhitespace,"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n RE_WHITESPACE\n" +isWritableProperty,"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n" +isWritablePropertyIn,"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n" +isWriteOnlyProperty,"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n" +isWriteOnlyPropertyIn,"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n" +iterAdd,"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n" +iterAdvance,"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n" +iterAny,"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n" +iterAnyBy,"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n" +iterator2array,"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value\n - index: iterated value index (zero-based)\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n" +iterator2arrayview,"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n" +iterator2arrayviewRight,"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n" +iteratorStream,"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n" +IteratorSymbol,"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n" +iterawgn,"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n" +iterawln,"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n" +iterawun,"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n" +iterBartlettHannPulse,"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n" +iterBartlettPulse,"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n" +iterConcat,"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n" +iterConstant,"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n" +iterCosineWave,"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n" +iterCounter,"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n" +itercugmean,"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n" +itercuhmean,"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n" +itercumax,"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n" +itercumaxabs,"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n" +itercumean,"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n" +itercumeanabs,"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n" +itercumeanabs2,"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n" +itercumidrange,"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n" +itercumin,"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n" +itercuminabs,"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n" +itercuprod,"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n" +itercurange,"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n" +itercusum,"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n" +itercusumabs,"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n" +itercusumabs2,"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n" +iterDedupe,"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n" +iterDedupeBy,"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value\n - sprev: previous source iterated value\n - dprev: previous downstream iterated value\n - index: source iteration index (zero-based)\n - acc: previous resolved value\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n" +iterDiracComb,"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n" +iterDivide,"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n" +iterEmpty,"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n" +iterEvery,"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n" +iterEveryBy,"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n" +iterFibonacci,"\niterFibonacci( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacci();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterNonFibonacci\n" +iterFill,"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n" +iterFilter,"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n" +iterFilterMap,"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n" +iterFirst,"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n" +iterFlatTopPulse,"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n" +iterFlow,"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n" +iterForEach,"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n" +iterHannPulse,"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n" +iterHead,"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n" +iterIntersection,"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n" +iterIntersectionByHash,"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n" +iterLanczosPulse,"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n" +iterLast,"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n" +iterLength,"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n" +iterMap,"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n" +iterMapN,"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values\n - index: iteration index (zero-based)\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n" +itermax,"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n" +itermaxabs,"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n" +itermean,"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n" +itermeanabs,"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n" +itermeanabs2,"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n" +itermidrange,"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n" +itermin,"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n" +iterminabs,"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n" +itermmax,"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n" +itermmaxabs,"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n" +itermmean,"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n" +itermmeanabs,"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n" +itermmeanabs2,"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n" +itermmidrange,"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n" +itermmin,"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n" +itermminabs,"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n" +iterMod,"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n" +itermprod,"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n" +itermrange,"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n" +itermsum,"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n" +itermsumabs,"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n" +itermsumabs2,"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n" +iterMultiply,"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n" +iterNone,"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n" +iterNoneBy,"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n" +iterNonFibonacci,"\niterNonFibonacci( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacci();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacci\n" +iterNth,"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n" +iterPeriodicSinc,"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n" +iterPipeline,"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n" +iterPop,"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n" +iterprod,"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n" +iterPulse,"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n" +iterPush,"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n" +iterrange,"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n" +iterReject,"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n" +iterReplicate,"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n" +iterReplicateBy,"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value\n - index: source iteration index (zero-based)\n - n: iteration index (zero-based)\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n" +iterSawtoothWave,"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n" +iterShift,"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n" +iterSineWave,"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n" +iterSlice,"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n" +iterSome,"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n" +iterSomeBy,"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n" +iterSquareWave,"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n" +iterstdev,"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n" +iterSubtract,"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n" +itersum,"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n" +itersumabs,"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n" +itersumabs2,"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n" +iterThunk,"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n" +iterTriangleWave,"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n" +iterUnion,"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n" +iterUnique,"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n" +iterUniqueBy,"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n" +iterUniqueByHash,"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n" +iterUnshift,"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n" +itervariance,"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n" +joinStream,"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n" kde2d,"" -keyBy,"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n" -keyByRight,"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n" -keysIn,"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n" +keyBy,"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n" +keyByRight,"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n" +keysIn,"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n" kruskalTest,"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups })\n\n" -kstest,"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 4839 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = {{alias:@stdlib/random/base/uniform}}.factory( 0.0, 1.0, { 'seed': 8798 })\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 })\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = {{alias:@stdlib/random/base/uniform}}.factory( 0.0, 1.0, { 'seed': 8798 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' })\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' })\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true })\n { pValue: ~1, statistic: 0.1, ... }\n\n" -LinkedList,"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n "snapshot", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n" -linspace,"\nlinspace( start, stop[, length] )\n Generates a linearly spaced numeric array.\n\n If a `length` is not provided, the default output array length is `100`.\n\n The output array is guaranteed to include the `start` and `stop` values.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Last array value.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = linspace( 0, 100, 6 )\n [ 0, 20, 40, 60, 80, 100 ]\n\n" -LIU_NEGATIVE_OPINION_WORDS_EN,"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. "Mining and Summarizing Customer\n Reviews." In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. "Opinion Observer:\n Analyzing and Comparing Opinions on the Web." In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n" -LIU_POSITIVE_OPINION_WORDS_EN,"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n" +kstest,"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 })\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 })\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' })\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' })\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true })\n { pValue: ~1, statistic: 0.1, ... }\n\n" +LinkedList,"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n" +linspace,"\nlinspace( start, stop[, length] )\n Generates a linearly spaced numeric array.\n\n If a `length` is not provided, the default output array length is `100`.\n\n The output array is guaranteed to include the `start` and `stop` values.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Last array value.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = linspace( 0, 100, 6 )\n [ 0, 20, 40, 60, 80, 100 ]\n\n See Also\n --------\n incrspace, logspace\n" +LIU_NEGATIVE_OPINION_WORDS_EN,"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n" +LIU_POSITIVE_OPINION_WORDS_EN,"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n" LN_HALF,"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n" -LN_PI,"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n" -LN_SQRT_TWO_PI,"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n" -LN_TWO_PI,"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n" -LN2,"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n" -LN10,"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n" -LOG2E,"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n" -LOG10E,"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n" -logspace,"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n" -lowercase,"\nlowercase( str )\n Converts a `string` to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n" -lowercaseKeys,"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n" -lowess,"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new {{alias:@stdlib/array/float64}}( 100 );\n > var y = new {{alias:@stdlib/array/float64}}( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*{{alias:@stdlib/random/base/randn}}() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = {{alias:@stdlib/plot/ctor}}( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n" -lpad,"\nlpad( str, len[, pad] )\n Left pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n" -ltrim,"\nltrim( str )\n Trims whitespace from the beginning of a `string`.\n\n "Whitespace" is defined as the following characters:\n\n - \f\n - \n\n - \r\n - \t\n - \v\n - \u0020\n - \u00a0\n - \u1680\n - \u2000-\u200a\n - \u2028\n - \u2029\n - \u202f\n - \u205f\n - \u3000\n - \ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \r\n\t Beep \t\t\n ' )\n 'Beep \t\t\n '\n\n" -MALE_FIRST_NAMES_EN,"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n" -mapFun,"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n" -mapFunAsync,"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - `index`: invocation index (starting from zero)\n - `next`: callback to be invoked upon function completion\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n" -mapKeys,"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n" -mapKeysAsync,"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `key`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `key`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `key`\n - `value`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `key`: transformed key\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n" -mapValues,"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n" -mapValuesAsync,"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `value`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `value`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `value`\n - `key`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `value`: transformed value\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n" -MAX_ARRAY_LENGTH,"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n" -MAX_TYPED_ARRAY_LENGTH,"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n" +LN_PI,"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n" +LN_SQRT_TWO_PI,"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n" +LN_TWO_PI,"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n" +LN2,"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n" +LN10,"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n" +LOG2E,"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n" +LOG10E,"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n" +logspace,"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n" +lowercase,"\nlowercase( str )\n Converts a `string` to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n" +lowercaseKeys,"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n" +lowess,"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n" +lpad,"\nlpad( str, len[, pad] )\n Left pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n" +ltrim,"\nltrim( str )\n Trims whitespace from the beginning of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \f\n - \n\n - \r\n - \t\n - \v\n - \u0020\n - \u00a0\n - \u1680\n - \u2000-\u200a\n - \u2028\n - \u2029\n - \u202f\n - \u205f\n - \u3000\n - \ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \r\n\t Beep \t\t\n ' )\n 'Beep \t\t\n '\n\n See Also\n --------\n trim, rtrim\n" +MALE_FIRST_NAMES_EN,"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n" +mapFun,"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n" +mapFunAsync,"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - `index`: invocation index (starting from zero)\n - `next`: callback to be invoked upon function completion\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n" +mapKeys,"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n" +mapKeysAsync,"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `key`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `key`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `key`\n - `value`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `key`: transformed key\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n" +mapValues,"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n" +mapValuesAsync,"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `value`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `value`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `value`\n - `key`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `value`: transformed value\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n" +MAX_ARRAY_LENGTH,"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n" +MAX_TYPED_ARRAY_LENGTH,"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n" memoize,"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n" -merge,"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n" +merge,"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n" MILLISECONDS_IN_DAY,"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n" MILLISECONDS_IN_HOUR,"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n" MILLISECONDS_IN_MINUTE,"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n" @@ -1508,379 +1508,379 @@ MINARD_NAPOLEONS_MARCH,"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data MINUTES_IN_DAY,"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n" MINUTES_IN_HOUR,"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n" MINUTES_IN_WEEK,"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n" -minutesInMonth,"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n" -minutesInYear,"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n" +minutesInMonth,"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n" +minutesInYear,"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n" MOBY_DICK,"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier)\n - title: chapter title (if available; otherwise, empty)\n - text: chapter text\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n" MONTH_NAMES_EN,"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n" MONTHS_IN_YEAR,"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n" moveProperty,"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n" -namedtypedtuple,"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( {{alias:@stdlib/array/float64}}[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...[, elementN]]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element: number\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n" -nativeClass,"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n" -ndarray,"\nndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarray( 'generic', 2 )\n \n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n" -ndarrayCastingModes,"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types\n - 'equiv': allow casting between identical and byte swapped types\n - 'safe': only allow "safe" casts\n - 'same-kind': allow "safe" casts and casts within the same kind (e.g.,\n between signed integers or between floats)\n - 'unsafe': allow casting between all types (including between integers and\n floats)\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'same-kind', 'unsafe' ]\n\n" -ndarrayDataTypes,"\nndarrayDataTypes()\n Returns a list of ndarray data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n \n\n" -ndarrayIndexModes,"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'clamp', 'wrap' ]\n\n" -ndarrayMemoized,"\nndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarrayMemoized( 'generic', 2 )\n \n > var f = ndarrayMemoized( 'generic', 2 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n" -ndarrayMinDataType,"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest "kind" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n" -ndarrayNextDataType,"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n" -ndarrayOrders,"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n" -ndarrayPromotionRules,"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest "kind" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n ndarray data type.\n\n dtype2: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n" -ndarraySafeCasts,"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n" -ndarraySameKindCasts,"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same "kind".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same "kind".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n" +namedtypedtuple,"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( Float64Array[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...[, elementN]]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element: number\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n" +nativeClass,"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n" +ndarray,"\nndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarray( 'generic', 2 )\n \n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n array\n" +ndarrayCastingModes,"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types\n - 'equiv': allow casting between identical and byte swapped types\n - 'safe': only allow \"safe\" casts\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats)\n - 'unsafe': allow casting between all types (including between integers and\n floats)\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n" +ndarrayDataTypes,"\nndarrayDataTypes()\n Returns a list of ndarray data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n" +ndarrayIndexModes,"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n" +ndarrayMemoized,"\nndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarrayMemoized( 'generic', 2 )\n \n > var f = ndarrayMemoized( 'generic', 2 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n array, ndarray\n" +ndarrayMinDataType,"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n" +ndarrayNextDataType,"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n" +ndarrayOrders,"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n" +ndarrayPromotionRules,"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n ndarray data type.\n\n dtype2: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n" +ndarraySafeCasts,"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n" +ndarraySameKindCasts,"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n" NIGHTINGALES_ROSE,"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son. .\n\n" -NINF,"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n" +NINF,"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n" NODE_VERSION,"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n" -none,"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n" -noneBy,"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n" -noneByAsync,"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n" -noneByRight,"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n" -noneByRightAsync,"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n" -nonEnumerableProperties,"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n" -nonEnumerablePropertiesIn,"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n" -nonEnumerablePropertyNames,"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n" -nonEnumerablePropertyNamesIn,"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n" -nonEnumerablePropertySymbols,"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n" -nonEnumerablePropertySymbolsIn,"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n" +none,"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n" +noneBy,"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n" +noneByAsync,"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n" +noneByRight,"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n" +noneByRightAsync,"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n" +nonEnumerableProperties,"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n" +nonEnumerablePropertiesIn,"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n" +nonEnumerablePropertyNames,"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n" +nonEnumerablePropertyNamesIn,"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n" +nonEnumerablePropertySymbols,"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n" +nonEnumerablePropertySymbolsIn,"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n" noop,"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n" now,"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n" NUM_CPUS,"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n" Number,"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n" -objectEntries,"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n" -objectEntriesIn,"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n" -objectFromEntries,"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n" -objectInverse,"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n" -objectInverseBy,"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n" -objectKeys,"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n" -objectValues,"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n" -objectValuesIn,"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n" -omit,"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n" -omitBy,"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n" +objectEntries,"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n" +objectEntriesIn,"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n" +objectFromEntries,"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n" +objectInverse,"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n" +objectInverseBy,"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n" +objectKeys,"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, objectValues\n" +objectValues,"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n" +objectValuesIn,"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n" +omit,"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n" +omitBy,"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n" openURL,"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n" -PACE_BOSTON_HOUSE_PRICES,"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number\n - town: town name\n - town_id: town identifier\n - tract: tract identifier\n - lon: longitude\n - lat: latitude\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. "Hedonic housing prices and\n the demand for clean air." _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. "On the Harrison and Rubinfeld\n Data." _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. "Using the Spatial\n Configuration of the Data to Improve Estimation." _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n" -pad,"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' })\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' })\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n" -papply,"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n" -papplyRight,"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n" +PACE_BOSTON_HOUSE_PRICES,"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number\n - town: town name\n - town_id: town identifier\n - tract: tract identifier\n - lon: longitude\n - lat: latitude\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n" +pad,"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' })\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' })\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n" +papply,"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n" +papplyRight,"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n" parallel,"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n Examples\n --------\n > function done( error ) { if ( error ) { throw error; } };\n > var files = [ './a.js', './b.js' ];\n > parallel( files, done );\n\n // Specify the number of workers:\n > var opts = { 'workers': 8 };\n > parallel( files, opts, done );\n\n" -parseJSON,"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{"beep":"boop"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{"beep":"boop","a":"b"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n" -PATH_DELIMITER,"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\Windows\\system32;C:\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\Windows\system32', 'C:\\Windows' ]\n\n" -PATH_DELIMITER_POSIX,"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n" -PATH_DELIMITER_WIN32,"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\Windows\\system32;C:\\Windows;C:\\Program Files\\node\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\Windows\\system32', 'C:\\Windows', 'C:\\Program Files\\node\\' ]\n\n" -PATH_SEP,"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\bar\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n" -PATH_SEP_POSIX,"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n" -PATH_SEP_WIN32,"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\'\n > var parts = 'foo\\bar\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n" -pcorrtest,"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = {{alias:@stdlib/random/base/normal}}( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + {{alias:@stdlib/random/base/normal}}( 0.0,\n ... {{alias:@stdlib/math/base/special/sqrt}}( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n" +parseJSON,"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n" +PATH_DELIMITER,"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\Windows\\system32;C:\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\Windows\system32', 'C:\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n" +PATH_DELIMITER_POSIX,"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n" +PATH_DELIMITER_WIN32,"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\Windows\\system32;C:\\Windows;C:\\Program Files\\node\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\Windows\\system32', 'C:\\Windows', 'C:\\Program Files\\node\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n" +PATH_SEP,"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\bar\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n" +PATH_SEP_POSIX,"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n" +PATH_SEP_WIN32,"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\'\n > var parts = 'foo\\bar\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n" +pcorrtest,"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n" percentEncode,"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n" PHI,"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n" -PI,"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n" -PI_SQUARED,"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n" -pick,"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n" -pickBy,"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n" -PINF,"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n" -pkg2alias,"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n\n" -pkg2related,"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n\n" -PLATFORM,"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n" -plot,"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n" -Plot,"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n" -pluck,"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n" -pop,"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n" -prepend,"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n" -properties,"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n" -propertiesIn,"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n" -propertyDescriptor,"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n" -propertyDescriptorIn,"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n" -propertyDescriptors,"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n" -propertyDescriptorsIn,"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n" -propertyNames,"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n" -propertyNamesIn,"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n" -propertySymbols,"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n" -propertySymbolsIn,"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n" -Proxy,"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following "traps" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n" -push,"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n" -quarterOfYear,"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n" -random.iterators.arcsine,"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.bernoulli,"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.beta,"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.betaprime,"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.binomial,"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.boxMuller,"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.cauchy,"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.chi,"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.chisquare,"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.cosine,"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.discreteUniform,"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.erlang,"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.exponential,"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.f,"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.frechet,"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.gamma,"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.geometric,"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.gumbel,"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.hypergeometric,"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.improvedZiggurat,"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.invgamma,"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.kumaraswamy,"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.laplace,"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.levy,"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.logistic,"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.lognormal,"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.minstd,"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the "randomness quality" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.minstdShuffle,"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the "randomness\n quality" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.mt19937,"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.negativeBinomial,"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.normal,"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.pareto1,"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.poisson,"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.randi,"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.randn,"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.randu,"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.rayleigh,"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.t,"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.triangular,"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.uniform,"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.iterators.weibull,"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n" -random.streams.arcsine,"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.bernoulli,"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.beta,"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.betaprime,"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.binomial,"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.boxMuller,"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.cauchy,"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.chi,"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.chisquare,"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.cosine,"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.discreteUniform,"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.erlang,"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.exponential,"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.f,"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.gamma,"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.geometric,"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.gumbel,"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.improvedZiggurat,"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.invgamma,"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.kumaraswamy,"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.laplace,"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.levy,"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.logistic,"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.lognormal,"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.minstd,"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the "randomness quality" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.minstdShuffle,"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the "randomness\n quality" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.mt19937,"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.negativeBinomial,"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.normal,"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.pareto1,"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.poisson,"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.randi,"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.randn,"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.randu,"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an "objectMode" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.rayleigh,"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.t,"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.uniform,"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -random.streams.weibull,"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an "objectMode" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" +PI,"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n" +PI_SQUARED,"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n" +pick,"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n" +pickBy,"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n" +PINF,"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n" +pkg2alias,"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n" +pkg2related,"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n" +PLATFORM,"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n" +plot,"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n" +Plot,"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n" +pluck,"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n" +pop,"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n" +prepend,"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n" +properties,"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n" +propertiesIn,"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n" +propertyDescriptor,"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n" +propertyDescriptorIn,"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n" +propertyDescriptors,"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n" +propertyDescriptorsIn,"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n" +propertyNames,"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n" +propertyNamesIn,"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n" +propertySymbols,"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n" +propertySymbolsIn,"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n" +Proxy,"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n" +push,"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n" +quarterOfYear,"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n" +random.iterators.arcsine,"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n" +random.iterators.bernoulli,"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n" +random.iterators.beta,"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n" +random.iterators.betaprime,"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n" +random.iterators.binomial,"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n" +random.iterators.boxMuller,"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n" +random.iterators.cauchy,"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n" +random.iterators.chi,"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n" +random.iterators.chisquare,"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n" +random.iterators.cosine,"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n" +random.iterators.discreteUniform,"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n" +random.iterators.erlang,"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n" +random.iterators.exponential,"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n" +random.iterators.f,"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n" +random.iterators.frechet,"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n" +random.iterators.gamma,"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n" +random.iterators.geometric,"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n" +random.iterators.gumbel,"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n" +random.iterators.hypergeometric,"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n" +random.iterators.improvedZiggurat,"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n" +random.iterators.invgamma,"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n" +random.iterators.kumaraswamy,"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n" +random.iterators.laplace,"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n" +random.iterators.levy,"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n" +random.iterators.logistic,"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n" +random.iterators.lognormal,"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n" +random.iterators.minstd,"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n" +random.iterators.minstdShuffle,"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n" +random.iterators.mt19937,"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n" +random.iterators.negativeBinomial,"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n" +random.iterators.normal,"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n" +random.iterators.pareto1,"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n" +random.iterators.poisson,"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n" +random.iterators.randi,"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n" +random.iterators.randn,"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n" +random.iterators.randu,"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n" +random.iterators.rayleigh,"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n" +random.iterators.t,"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n" +random.iterators.triangular,"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n" +random.iterators.uniform,"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n" +random.iterators.weibull,"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n" +random.streams.arcsine,"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n" +random.streams.bernoulli,"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n" +random.streams.beta,"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n" +random.streams.betaprime,"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n" +random.streams.binomial,"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n" +random.streams.boxMuller,"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n" +random.streams.cauchy,"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n" +random.streams.chi,"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n" +random.streams.chisquare,"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n" +random.streams.cosine,"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n" +random.streams.discreteUniform,"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n" +random.streams.erlang,"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n" +random.streams.exponential,"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n" +random.streams.f,"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n" +random.streams.gamma,"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n" +random.streams.geometric,"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n" +random.streams.gumbel,"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n" +random.streams.improvedZiggurat,"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n" +random.streams.invgamma,"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n" +random.streams.kumaraswamy,"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n" +random.streams.laplace,"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n" +random.streams.levy,"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n" +random.streams.logistic,"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n" +random.streams.lognormal,"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n" +random.streams.minstd,"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n" +random.streams.minstdShuffle,"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n" +random.streams.mt19937,"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n" +random.streams.negativeBinomial,"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n" +random.streams.normal,"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n" +random.streams.pareto1,"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n" +random.streams.poisson,"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n" +random.streams.randi,"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n" +random.streams.randn,"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n" +random.streams.randu,"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n" +random.streams.rayleigh,"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n" +random.streams.t,"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n" +random.streams.uniform,"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n" +random.streams.weibull,"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n" ranks,"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n" -RE_BASENAME,"\nRE_BASENAME\n Regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_BASENAME.posix\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nRE_BASENAME.win32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n 'index.js'\n\n" -RE_BASENAME_POSIX,"\nRE_BASENAME_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n" -RE_BASENAME_WINDOWS,"\nRE_BASENAME_WINDOWS\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME_WINDOWS.exec( '\\foo\\bar\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\bar\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n" +RE_BASENAME,"\nRE_BASENAME\n Regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_BASENAME.posix\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nRE_BASENAME.win32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n RE_BASENAME_POSIX, RE_BASENAME_WINDOWS\n" +RE_BASENAME_POSIX,"\nRE_BASENAME_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_BASENAME, RE_BASENAME_WINDOWS\n" +RE_BASENAME_WINDOWS,"\nRE_BASENAME_WINDOWS\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME_WINDOWS.exec( '\\foo\\bar\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\bar\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_BASENAME, RE_BASENAME_POSIX\n" RE_COLOR_HEXADECIMAL,"\nRE_COLOR_HEXADECIMAL\n Regular expression to match a hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.test( '000' )\n false\n > bool = RE_COLOR_HEXADECIMAL.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.shorthand\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'ffffff' )\n false\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.either\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.either.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( 'beep' )\n false\n\n" RE_DECIMAL_NUMBER,"\nRE_DECIMAL_NUMBER\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var bool = RE_DECIMAL_NUMBER.test( '1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '-1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0' )\n false\n > bool = RE_DECIMAL_NUMBER.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = new RegExp( RE_DECIMAL_NUMBER.source, 'g' );\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\n" -RE_DIRNAME,"\nRE_DIRNAME\n Regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_DIRNAME.posix\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nRE_DIRNAME.win32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n" -RE_DIRNAME_POSIX,"\nRE_DIRNAME_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( './' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n" -RE_DIRNAME_WINDOWS,"\nRE_DIRNAME_WINDOWS\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_WINDOWS.exec( 'foo\\bar\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_WINDOWS.exec( '\\foo\\bar\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n" +RE_DIRNAME,"\nRE_DIRNAME\n Regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_DIRNAME.posix\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nRE_DIRNAME.win32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n RE_DIRNAME_POSIX, RE_DIRNAME_WINDOWS, dirname\n" +RE_DIRNAME_POSIX,"\nRE_DIRNAME_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( './' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_DIRNAME, RE_DIRNAME_WINDOWS, dirname\n" +RE_DIRNAME_WINDOWS,"\nRE_DIRNAME_WINDOWS\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_WINDOWS.exec( 'foo\\bar\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_WINDOWS.exec( '\\foo\\bar\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_DIRNAME, RE_DIRNAME_POSIX, dirname\n" RE_EOL,"\nRE_EOL\n Regular expression to match a newline character sequence: /\r?\n/.\n\n Examples\n --------\n > var bool = RE_EOL.test( '\n' )\n true\n > bool = RE_EOL.test( '\r\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n false\n\n" RE_EXTENDED_LENGTH_PATH,"\nRE_EXTENDED_LENGTH_PATH\n Regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\?\`.\n\n Examples\n --------\n > var path = '\\\\?\\C:\\foo\\bar';\n > var bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = '\\\\?\\UNC\\server\\share';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = 'C:\\foo\\bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n\n" -RE_EXTNAME,"\nRE_EXTNAME\n Regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_EXTNAME.posix\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nRE_EXTNAME.win32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n '.js'\n\n" -RE_EXTNAME_POSIX,"\nRE_EXTNAME_POSIX\n Regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( '.' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( './' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n" -RE_EXTNAME_WINDOWS,"\nRE_EXTNAME_WINDOWS\n Regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_WINDOWS.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_WINDOWS.exec( '\\foo\\bar\\file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'beep\\boop.' )[ 1 ]\n '.'\n > ext = RE_EXTNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n" -RE_FILENAME,"\nRE_FILENAME\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_FILENAME.posix\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nRE_FILENAME.win32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\foo\\bar\\index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ 'C:\\foo\\bar\\index.js', 'C:', '\\', 'foo\\bar\\', 'index.js', '.js' ]\n\n" -RE_FILENAME_POSIX,"\nRE_FILENAME_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_POSIX.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_POSIX.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( './' ).slice()\n [ './', '', '.', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n" -RE_FILENAME_WINDOWS,"\nRE_FILENAME_WINDOWS\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_WINDOWS.exec( 'C:\\foo\\bar\\index.js' ).slice()\n [ 'C:\\foo\\bar\\index.js', 'C:', '\\', 'foo\\bar\\', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\foo\\bar\\.gitignore' ).slice()\n [ '\\foo\\bar\\.gitignore', '', '\\', 'foo\\bar\\', '.gitignore', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'foo\\file.pdf' ).slice()\n [ 'foo\\file.pdf', '', '', 'foo\\', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\foo\\bar\\file' ).slice()\n [ '\\foo\\bar\\file', '', '\\', 'foo\\bar\\', 'file', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( './' ).slice()\n [ './', '', '', '.', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n" -RE_FUNCTION_NAME,"\nRE_FUNCTION_NAME\n Regular expression to capture a function name.\n\n Examples\n --------\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n" -RE_NATIVE_FUNCTION,"\nRE_NATIVE_FUNCTION\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = RE_NATIVE_FUNCTION.test( Date.toString() )\n true\n > bool = RE_NATIVE_FUNCTION.test( (function noop() {}).toString() )\n false\n\n" -RE_REGEXP,"\nRE_REGEXP\n Regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Examples\n --------\n > var bool = RE_REGEXP.test( '/^beep$/' )\n true\n > bool = RE_REGEXP.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE_REGEXP.test( '/^\/([^\/]+)\/(.*)$/' )\n false\n > bool = RE_REGEXP.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n true\n\n" -RE_UNC_PATH,"\nRE_UNC_PATH\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\server\\share\\foo\\bar\\baz:a:b';\n > var bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar\\baz::b';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar\\baz:a';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar\\baz';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'beep boop \\\\server\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz:a:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz::';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz:a:b:c';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '//server/share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = './foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE_UNC_PATH.test( path )\n false\n\n" -RE_UTF16_SURROGATE_PAIR,"\nRE_UTF16_SURROGATE_PAIR\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var bool = RE_UTF16_SURROGATE_PAIR.test( 'abc\uD800\uDC00def' )\n true\n > bool = RE_UTF16_SURROGATE_PAIR.test( 'abcdef' )\n false\n\n" -RE_UTF16_UNPAIRED_SURROGATE,"\nRE_UTF16_UNPAIRED_SURROGATE\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var bool = RE_UTF16_UNPAIRED_SURROGATE.test( 'abc' )\n false\n > bool = RE_UTF16_UNPAIRED_SURROGATE.test( '\uD800' )\n true\n\n" -RE_WHITESPACE,"\nRE_WHITESPACE\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space ("WSpace=Y","WS")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property "WSpace=Y" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var bool = RE_WHITESPACE.test( '\n' )\n true\n > bool = RE_WHITESPACE.test( ' ' )\n true\n > bool = RE_WHITESPACE.test( 'a' )\n false\n\n" -readDir,"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n" -readFile,"\nreadFile( file[, options,] clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n" +RE_EXTNAME,"\nRE_EXTNAME\n Regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_EXTNAME.posix\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nRE_EXTNAME.win32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n RE_EXTNAME_POSIX, RE_EXTNAME_WINDOWS, extname\n" +RE_EXTNAME_POSIX,"\nRE_EXTNAME_POSIX\n Regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( '.' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( './' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_EXTNAME, RE_EXTNAME_WINDOWS, extname\n" +RE_EXTNAME_WINDOWS,"\nRE_EXTNAME_WINDOWS\n Regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_WINDOWS.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_WINDOWS.exec( '\\foo\\bar\\file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'beep\\boop.' )[ 1 ]\n '.'\n > ext = RE_EXTNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_EXTNAME, RE_EXTNAME_POSIX, extname\n" +RE_FILENAME,"\nRE_FILENAME\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_FILENAME.posix\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nRE_FILENAME.win32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\foo\\bar\\index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ 'C:\\foo\\bar\\index.js', 'C:', '\\', 'foo\\bar\\', 'index.js', '.js' ]\n\n See Also\n --------\n RE_FILENAME_POSIX, RE_FILENAME_WINDOWS\n" +RE_FILENAME_POSIX,"\nRE_FILENAME_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_POSIX.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_POSIX.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( './' ).slice()\n [ './', '', '.', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n See Also\n --------\n RE_FILENAME, RE_FILENAME_WINDOWS\n" +RE_FILENAME_WINDOWS,"\nRE_FILENAME_WINDOWS\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_WINDOWS.exec( 'C:\\foo\\bar\\index.js' ).slice()\n [ 'C:\\foo\\bar\\index.js', 'C:', '\\', 'foo\\bar\\', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\foo\\bar\\.gitignore' ).slice()\n [ '\\foo\\bar\\.gitignore', '', '\\', 'foo\\bar\\', '.gitignore', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'foo\\file.pdf' ).slice()\n [ 'foo\\file.pdf', '', '', 'foo\\', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\foo\\bar\\file' ).slice()\n [ '\\foo\\bar\\file', '', '\\', 'foo\\bar\\', 'file', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( './' ).slice()\n [ './', '', '', '.', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n See Also\n --------\n RE_FILENAME, RE_FILENAME_POSIX\n" +RE_FUNCTION_NAME,"\nRE_FUNCTION_NAME\n Regular expression to capture a function name.\n\n Examples\n --------\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n See Also\n --------\n functionName\n" +RE_NATIVE_FUNCTION,"\nRE_NATIVE_FUNCTION\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = RE_NATIVE_FUNCTION.test( Date.toString() )\n true\n > bool = RE_NATIVE_FUNCTION.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n RE_FUNCTION_NAME, functionName\n" +RE_REGEXP,"\nRE_REGEXP\n Regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Examples\n --------\n > var bool = RE_REGEXP.test( '/^beep$/' )\n true\n > bool = RE_REGEXP.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE_REGEXP.test( '/^\/([^\/]+)\/(.*)$/' )\n false\n > bool = RE_REGEXP.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n true\n\n See Also\n --------\n reFromString\n" +RE_UNC_PATH,"\nRE_UNC_PATH\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\server\\share\\foo\\bar\\baz:a:b';\n > var bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar\\baz::b';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar\\baz:a';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar\\baz';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo\\bar';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share\\foo';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\share';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'beep boop \\\\server\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz:a:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz::';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\baz:a:b:c';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\server\\share\\foo\\bar\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '//server/share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = './foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE_UNC_PATH.test( path )\n false\n\n See Also\n --------\n isUNCPath\n" +RE_UTF16_SURROGATE_PAIR,"\nRE_UTF16_SURROGATE_PAIR\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var bool = RE_UTF16_SURROGATE_PAIR.test( 'abc\uD800\uDC00def' )\n true\n > bool = RE_UTF16_SURROGATE_PAIR.test( 'abcdef' )\n false\n\n See Also\n --------\n RE_UTF16_UNPAIRED_SURROGATE\n" +RE_UTF16_UNPAIRED_SURROGATE,"\nRE_UTF16_UNPAIRED_SURROGATE\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var bool = RE_UTF16_UNPAIRED_SURROGATE.test( 'abc' )\n false\n > bool = RE_UTF16_UNPAIRED_SURROGATE.test( '\uD800' )\n true\n\n See Also\n --------\n RE_UTF16_SURROGATE_PAIR\n" +RE_WHITESPACE,"\nRE_WHITESPACE\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var bool = RE_WHITESPACE.test( '\n' )\n true\n > bool = RE_WHITESPACE.test( ' ' )\n true\n > bool = RE_WHITESPACE.test( 'a' )\n false\n\n See Also\n --------\n isWhitespace\n" +readDir,"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n" +readFile,"\nreadFile( file[, options,] clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, readDir, readJSON, writeFile\n" readFileList,"\nreadFileList( filepaths[, options,] clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path\n - data: file contents as either a Buffer or string\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n" -readJSON,"\nreadJSON( file[, options,] clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n" -readWASM,"\nreadWASM( file, [options,] clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n" -real,"\nreal( z )\n Returns the real component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n" -realmax,"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n" -realmin,"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n" -reduce,"\nreduce( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) { return acc + v; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduce( arr, 0, sum )\n 6.0\n\n" -reduceAsync,"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n" -reduceRight,"\nreduceRight( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) {\n ... console.log( '%s: %d', acc, v );\n ... return acc + v;\n ... };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduceRight( arr, 0, sum );\n 2: 3.0\n 1: 2.0\n 0: 1.0\n > out\n 6.0\n\n" -reduceRightAsync,"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n" +readJSON,"\nreadJSON( file[, options,] clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n" +readWASM,"\nreadWASM( file, [options,] clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n" +real,"\nreal( z )\n Returns the real component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n" +realmax,"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n" +realmin,"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n" +reduce,"\nreduce( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) { return acc + v; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduce( arr, 0, sum )\n 6.0\n\n See Also\n --------\n forEach, reduceAsync, reduceRight\n" +reduceAsync,"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n" +reduceRight,"\nreduceRight( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) {\n ... console.log( '%s: %d', acc, v );\n ... return acc + v;\n ... };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduceRight( arr, 0, sum );\n 2: 3.0\n 1: 2.0\n 0: 1.0\n > out\n 6.0\n\n See Also\n --------\n forEachRight, reduce, reduceRightAsync\n" +reduceRightAsync,"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n" reFromString,"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n" -reim,"\nreim( z )\n Returns the real and imaginary components of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n" -removeFirst,"\nremoveFirst( str )\n Removes the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n\n" -removeLast,"\nremoveLast( str )\n Removes the last character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n\n" -removePunctuation,"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' "\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: "A leader leads by example not by force."';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\'"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n" +reim,"\nreim( z )\n Returns the real and imaginary components of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n" +removeFirst,"\nremoveFirst( str )\n Removes the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n\n See Also\n --------\n removeLast\n" +removeLast,"\nremoveLast( str )\n Removes the last character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n\n See Also\n --------\n removeFirst\n" +removePunctuation,"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n" removeUTF8BOM,"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\ufeffbeep' )\n 'beep'\n\n" removeWords,"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n" -rename,"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n" -reorderArguments,"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n" -repeat,"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n" +rename,"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n" +reorderArguments,"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n reverseArguments\n" +repeat,"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n" replace,"\nreplace( str, search, newval )\n Replaces `search` occurrences with a replacement `string`.\n\n When provided a `string` as the `search` value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n" rescape,"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\[A\\-Z\\]\\*'\n\n" resolveParentPath,"\nresolveParentPath( path[, options,] clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n" -reverseArguments,"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n" +reverseArguments,"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n reorderArguments\n" reverseString,"\nreverseString( str )\n Reverses a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n" -reviveBasePRNG,"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( {{alias:@stdlib/random/base/mt19937}} );\n > var r = {{alias:@stdlib/utils/parse-json}}( str, reviveBasePRNG )\n \n\n" -reviveBuffer,"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer)\n - data: buffer data as an array of integers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{"type":"Buffer","data":[5,3]}';\n > var buf = {{alias:@stdlib/utils/parse-json}}( str, reviveBuffer )\n [ 5, 3 ]\n\n" -reviveComplex,"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., "Complex128", "Complex64")\n - re: real component (number)\n - im: imaginary component (number)\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{"type":"Complex128","re":5,"im":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex )\n \n\n" -reviveComplex64,"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{"type":"Complex64","re":5,"im":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex64 )\n \n\n" -reviveComplex128,"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{"type":"Complex128","re":5,"im":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex128 )\n \n\n" -reviveError,"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{"type":"TypeError","message":"beep"}';\n > var err = JSON.parse( str, reviveError )\n \n\n" -reviveTypedArray,"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., "Float64Array", "Int8Array")\n - data: typed array data as an array of numbers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{"type":"Float64Array","data":[5,3]}';\n > var arr = {{alias:@stdlib/utils/parse-json}}( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n" -rpad,"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n" -rtrim,"\nrtrim( str )\n Trims whitespace from the end of a `string`.\n\n "Whitespace" is defined as the following characters:\n\n - \f\n - \n\n - \r\n - \t\n - \v\n - \u0020\n - \u00a0\n - \u1680\n - \u2000-\u200a\n - \u2028\n - \u2029\n - \u202f\n - \u205f\n - \u3000\n - \ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \t\t\n Beep \r\n\t ' )\n ' \t\t\n Beep'\n\n" -safeintmax,"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n" -safeintmin,"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n" +reviveBasePRNG,"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n" +reviveBuffer,"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer)\n - data: buffer data as an array of integers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n" +reviveComplex,"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\")\n - re: real component (number)\n - im: imaginary component (number)\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n" +reviveComplex64,"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n" +reviveComplex128,"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n" +reviveError,"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n" +reviveTypedArray,"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\")\n - data: typed array data as an array of numbers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n" +rpad,"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n" +rtrim,"\nrtrim( str )\n Trims whitespace from the end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \f\n - \n\n - \r\n - \t\n - \v\n - \u0020\n - \u00a0\n - \u1680\n - \u2000-\u200a\n - \u2028\n - \u2029\n - \u202f\n - \u205f\n - \u3000\n - \ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \t\t\n Beep \r\n\t ' )\n ' \t\t\n Beep'\n\n See Also\n --------\n ltrim, trim\n" +safeintmax,"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n" +safeintmin,"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n" sample,"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 })\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 })\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 })\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false })\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs })\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false })\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 });\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 });\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n" -SAVOY_STOPWORDS_FIN,"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" -SAVOY_STOPWORDS_FR,"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" -SAVOY_STOPWORDS_GER,"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" -SAVOY_STOPWORDS_IT,"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" -SAVOY_STOPWORDS_POR,"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" -SAVOY_STOPWORDS_SP,"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" -SAVOY_STOPWORDS_SWE,"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. "IR Multilingual Resources at UniNE."\n .\n\n" +SAVOY_STOPWORDS_FIN,"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n" +SAVOY_STOPWORDS_FR,"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n" +SAVOY_STOPWORDS_GER,"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n" +SAVOY_STOPWORDS_IT,"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n" +SAVOY_STOPWORDS_POR,"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n" +SAVOY_STOPWORDS_SP,"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n" +SAVOY_STOPWORDS_SWE,"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n" SECONDS_IN_DAY,"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n" SECONDS_IN_HOUR,"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n" SECONDS_IN_MINUTE,"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n" SECONDS_IN_WEEK,"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n" -secondsInMonth,"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n" -secondsInYear,"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n" -setConfigurableReadOnly,"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n" -setConfigurableReadOnlyAccessor,"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n" -setConfigurableReadWriteAccessor,"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n" -setConfigurableWriteOnlyAccessor,"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n" -setMemoizedReadOnly,"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n" -setNonEnumerableProperty,"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > {{alias:@stdlib/utils/keys}}( obj )\n []\n\n" -setNonEnumerableReadOnly,"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n" -setNonEnumerableReadOnlyAccessor,"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n" -setNonEnumerableReadWriteAccessor,"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n" -setNonEnumerableWriteOnlyAccessor,"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n" -setReadOnly,"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n" -setReadOnlyAccessor,"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n" -setReadWriteAccessor,"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n" -setWriteOnlyAccessor,"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n" -SharedArrayBuffer,"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n" -shift,"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n" -shuffle,"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' });\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' });\n > bool = ( arr === out )\n false\n\n" -sizeOf,"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - complex128: 128-bit complex numbers\n - complex64: 64-bit complex numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n" -some,"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n" -someBy,"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n" -someByAsync,"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n" -someByRight,"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n" -someByRightAsync,"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n" +secondsInMonth,"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n" +secondsInYear,"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n" +setConfigurableReadOnly,"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n" +setConfigurableReadOnlyAccessor,"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n" +setConfigurableReadWriteAccessor,"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n" +setConfigurableWriteOnlyAccessor,"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n" +setMemoizedReadOnly,"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n" +setNonEnumerableProperty,"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n" +setNonEnumerableReadOnly,"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n" +setNonEnumerableReadOnlyAccessor,"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n" +setNonEnumerableReadWriteAccessor,"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n" +setNonEnumerableWriteOnlyAccessor,"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n" +setReadOnly,"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n" +setReadOnlyAccessor,"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n" +setReadWriteAccessor,"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n" +setWriteOnlyAccessor,"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n" +SharedArrayBuffer,"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n" +shift,"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n" +shuffle,"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' });\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' });\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n" +sizeOf,"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - complex128: 128-bit complex numbers\n - complex64: 64-bit complex numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n" +some,"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n" +someBy,"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n" +someByAsync,"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n" +someByRight,"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n" +someByRightAsync,"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n" SOTU,"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year\n - name: President name\n - party: the President's political party\n - text: speech text\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n" -SPACHE_REVISED,"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. "A New Readability Formula for Primary-Grade Reading\n Materials." *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. "Assessing Readability." *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. "Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure." *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. "The assessment of linguistic difficulty in\n reading material." In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n" +SPACHE_REVISED,"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n" SPAM_ASSASSIN,"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group)\n - group: message group\n - checksum: object containing checksum info\n - text: message text (including headers)\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages)\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages)\n - hard-ham-1: harder to detect non-spam e-mails (250 messages)\n - spam-1: spam e-mails (500 messages)\n - spam-2: spam e-mails collected at a later date (1396 messages)\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5)\n - value: checksum value\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n" -SparklineBase,"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n" -sparsearray2iterator,"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n" -sparsearray2iteratorRight,"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n" -splitStream,"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\r?\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\nb\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\r?\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\nb\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an "objectMode" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\r?\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in "objectMode". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in "objectMode".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\nb\c' );\n > s.end();\n\n" -SQRT_EPS,"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n" -SQRT_HALF,"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n" -SQRT_HALF_PI,"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n" -SQRT_PHI,"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n" -SQRT_PI,"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n" +SparklineBase,"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n" +sparsearray2iterator,"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n" +sparsearray2iteratorRight,"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n" +splitStream,"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\r?\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\nb\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\r?\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\nb\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\r?\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\nb\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n" +SQRT_EPS,"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n" +SQRT_HALF,"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n" +SQRT_HALF_PI,"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n" +SQRT_PHI,"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n" +SQRT_PI,"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n" SQRT_THREE,"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n" -SQRT_TWO,"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n" -SQRT_TWO_PI,"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n" -Stack,"\nStack()\n Stack constructor.\n\n A stack is also referred to as a "last-in-first-out" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the "newest" stack value (i.e., the value which is "first-out").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n "snapshot", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the "oldest" stack value (i.e., the value which is "last-out").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current "first-out" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n" -startcase,"\nstartcase( str )\n Capitalizes the first letter of each word in an input `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n" -startsWith,"\nstartsWith( str, search[, position] )\n Tests if a `string` starts with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` starts with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n" +SQRT_TWO,"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n" +SQRT_TWO_PI,"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n" +Stack,"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n" +startcase,"\nstartcase( str )\n Capitalizes the first letter of each word in an input `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n" +startsWith,"\nstartsWith( str, search[, position] )\n Tests if a `string` starts with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` starts with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n" STOPWORDS_EN,"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n" -stridedarray2iterator,"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n" -stridedArrayStream,"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in "objectMode". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in "objectMode".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an "objectMode" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in "objectMode".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n" -string2buffer,"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n" -sub2ind,"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'wrap', the function wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n" -SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK,"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. "Labelled data collection for\n anomaly detection in wireless sensor networks." In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n" -SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK,"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. "Labelled data collection for\n anomaly detection in wireless sensor networks." In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n" +stridedarray2iterator,"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n" +stridedArrayStream,"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n" +string2buffer,"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n" +sub2ind,"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'wrap', the function wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n" +SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK,"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n" +SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK,"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n" Symbol,"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n" -tabulate,"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n" -tabulateBy,"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n" -tabulateByAsync,"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n" -tic,"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n" -timeit,"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` options is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \'Something went wrong.\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n "iterations": 1000000,\n "repeats": 3,\n "min": [ 0, 135734733 ], // [seconds,nanoseconds]\n "elapsed": 0.135734733, // seconds\n "rate": 7367311.062526641, // iterations/second\n "times": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n" -tmpdir,"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n" -toc,"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = {{alias:@stdlib/time/tic}}();\n > var delta = toc( start )\n [ , ]\n\n" +tabulate,"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n" +tabulateBy,"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n" +tabulateByAsync,"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n" +tic,"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n" +timeit,"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` options is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \'Something went wrong.\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n" +tmpdir,"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n" +toc,"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n" tokenize,"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n" -transformStream,"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an "objectMode" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in "objectMode".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in "objectMode". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n" -trim,"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n "Whitespace" is defined as the following characters:\n\n - \f\n - \n\n - \r\n - \t\n - \v\n - \u0020\n - \u00a0\n - \u1680\n - \u2000-\u200a\n - \u2028\n - \u2029\n - \u202f\n - \u205f\n - \u3000\n - \ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \t\t\n Beep \r\n\t ' )\n 'Beep'\n\n" -trycatch,"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( {{alias:@stdlib/random/base/randu}}() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n" -trycatchAsync,"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - result: function result\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object\n - result: either the result of `x` or the provided argument `y`\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n" +transformStream,"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n" +trim,"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \f\n - \n\n - \r\n - \t\n - \v\n - \u0020\n - \u00a0\n - \u1680\n - \u2000-\u200a\n - \u2028\n - \u2029\n - \u202f\n - \u205f\n - \u3000\n - \ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \t\t\n Beep \r\n\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n" +trycatch,"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n" +trycatchAsync,"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - result: function result\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object\n - result: either the result of `x` or the provided argument `y`\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n" tryFunction,"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n" tryRequire,"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n" -trythen,"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( {{alias:@stdlib/random/base/randu}}() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n" -trythenAsync,"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n" -ttest,"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory( 0.0, 2.0, { 'seed': 5776 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = {{alias:@stdlib/random/base/normal}}.factory( 1.0, 2.0, { 'seed': 786 });\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n" -ttest2,"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' });\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' })\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n" -TWO_PI,"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n" -typedarray,"\ntypedarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n" -typedarray2json,"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type\n - data: typed array data as a generic array\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n" -typedarrayComplexCtors,"\ntypedarrayComplexCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayComplexCtors( 'complex64' )\n \n > ctor = typedarrayComplexCtors( 'float32' )\n null\n\n" -typedarrayComplexDataTypes,"\ntypedarrayComplexDataTypes()\n Returns a list of complex typed array data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = typedarrayComplexDataTypes()\n \n\n" -typedarrayCtors,"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n" -typedarrayDataTypes,"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n" -typedarraypool,"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n" -typemax,"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n" -typemin,"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n" -typeOf,"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new {{alias:@stdlib/array/int8}}( 10 ) )\n 'int8array'\n > t = typeOf( new {{alias:@stdlib/array/uint8}}( 10 ) )\n 'uint8array'\n > t = typeOf( new {{alias:@stdlib/array/uint8c}}( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new {{alias:@stdlib/array/int16}}( 10 ) )\n 'int16array'\n > t = typeOf( new {{alias:@stdlib/array/uint16}}( 10 ) )\n 'uint16array'\n > t = typeOf( new {{alias:@stdlib/array/int32}}( 10 ) )\n 'int32array'\n > t = typeOf( new {{alias:@stdlib/array/uint32}}( 10 ) )\n 'uint32array'\n > t = typeOf( new {{alias:@stdlib/array/float32}}( 10 ) )\n 'float32array'\n > t = typeOf( new {{alias:@stdlib/array/float64}}( 10 ) )\n 'float64array'\n > t = typeOf( new {{alias:@stdlib/array/buffer}}( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new {{alias:@stdlib/buffer/ctor}}( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n" -UINT8_MAX,"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n" -UINT8_NUM_BYTES,"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n" -Uint8Array,"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" -Uint8ClampedArray,"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" -UINT16_MAX,"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n" -UINT16_NUM_BYTES,"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n" -Uint16Array,"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" -UINT32_MAX,"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n" -UINT32_NUM_BYTES,"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n" -Uint32Array,"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n" -umask,"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to "1", the corresponding initial file\n permission is disabled. If the mask contains a bit set to "0", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a "1" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where "classes" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n "symbols" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and "operator" may be one of\n\n - `+`: enable\n - `-`: disable\n - `=`: enable specified and disable unspecified permissions\n\n For example,\n\n - `u-w`: disable user write permissions\n - `u+w`: enable user write permissions\n - `u=w`: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates "all", which is the same as specifying "ugo". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n" -uncapitalize,"\nuncapitalize( str )\n Lowercases the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n" -uncapitalizeKeys,"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n" -uncurry,"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n" -uncurryRight,"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n" -UNICODE_MAX,"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n" -UNICODE_MAX_BMP,"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n" -UnicodeColumnChartSparkline,"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n" -UnicodeLineChartSparkline,"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n" -UnicodeSparkline,"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n" -UnicodeTristateChartSparkline,"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n" -UnicodeUpDownChartSparkline,"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n" -UnicodeWinLossChartSparkline,"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n" -unlink,"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n" -unshift,"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n" -until,"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n" -untilAsync,"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n" -untilEach,"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n" -untilEachRight,"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n" -unzip,"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n" -uppercase,"\nuppercase( str )\n Converts a `string` to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n" -uppercaseKeys,"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n" -US_STATES_ABBR,"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n" -US_STATES_CAPITALS,"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n" -US_STATES_CAPITALS_NAMES,"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n" -US_STATES_NAMES,"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n" -US_STATES_NAMES_CAPITALS,"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n" +trythen,"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n" +trythenAsync,"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n" +ttest,"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 });\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n" +ttest2,"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' });\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' })\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n" +TWO_PI,"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n" +typedarray,"\ntypedarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n" +typedarray2json,"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type\n - data: typed array data as a generic array\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n" +typedarrayComplexCtors,"\ntypedarrayComplexCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayComplexCtors( 'complex64' )\n \n > ctor = typedarrayComplexCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors\n" +typedarrayComplexDataTypes,"\ntypedarrayComplexDataTypes()\n Returns a list of complex typed array data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = typedarrayComplexDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, ndarrayDataTypes\n" +typedarrayCtors,"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n" +typedarrayDataTypes,"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n" +typedarraypool,"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n" +typemax,"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n" +typemin,"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n" +typeOf,"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n" +UINT8_MAX,"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n" +UINT8_NUM_BYTES,"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n" +Uint8Array,"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n" +Uint8ClampedArray,"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n" +UINT16_MAX,"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n" +UINT16_NUM_BYTES,"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n" +Uint16Array,"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n" +UINT32_MAX,"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n" +UINT32_NUM_BYTES,"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n" +Uint32Array,"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n" +umask,"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - `+`: enable\n - `-`: disable\n - `=`: enable specified and disable unspecified permissions\n\n For example,\n\n - `u-w`: disable user write permissions\n - `u+w`: enable user write permissions\n - `u=w`: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n" +uncapitalize,"\nuncapitalize( str )\n Lowercases the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n" +uncapitalizeKeys,"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n" +uncurry,"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n" +uncurryRight,"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n" +UNICODE_MAX,"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n" +UNICODE_MAX_BMP,"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n" +UnicodeColumnChartSparkline,"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n" +UnicodeLineChartSparkline,"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n" +UnicodeSparkline,"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n" +UnicodeTristateChartSparkline,"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n" +UnicodeUpDownChartSparkline,"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n" +UnicodeWinLossChartSparkline,"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n" +unlink,"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n" +unshift,"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n" +until,"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n" +untilAsync,"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n" +untilEach,"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n" +untilEachRight,"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n" +unzip,"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n" +uppercase,"\nuppercase( str )\n Converts a `string` to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n" +uppercaseKeys,"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n" +US_STATES_ABBR,"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n" +US_STATES_CAPITALS,"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n" +US_STATES_CAPITALS_NAMES,"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n" +US_STATES_NAMES,"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n" +US_STATES_NAMES_CAPITALS,"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n" utf16ToUTF8Array,"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n" -vartest,"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n" +vartest,"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n" waterfall,"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n" -whileAsync,"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n" -whileEach,"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n" -whileEachRight,"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n" -whilst,"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n" -writableProperties,"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n" -writablePropertiesIn,"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n" -writablePropertyNames,"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n" -writablePropertyNamesIn,"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n" -writablePropertySymbols,"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n" -writablePropertySymbolsIn,"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n" -writeFile,"\nwriteFile( file, data[, options,] clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n" -zip,"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n" -ztest,"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory( 0.0, 2.0, { 'seed': 212 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 });\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' })\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' })\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n" -ztest2,"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 })\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n" +whileAsync,"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n" +whileEach,"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n" +whileEachRight,"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n" +whilst,"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n" +writableProperties,"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n" +writablePropertiesIn,"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n" +writablePropertyNames,"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n" +writablePropertyNamesIn,"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n" +writablePropertySymbols,"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n" +writablePropertySymbolsIn,"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n" +writeFile,"\nwriteFile( file, data[, options,] clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n" +zip,"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n" +ztest,"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 });\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' })\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' })\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n" +ztest2,"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 })\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n" diff --git a/lib/node_modules/@stdlib/repl/help/data/data.json b/lib/node_modules/@stdlib/repl/help/data/data.json index d2944339f5e1..1ae4a5fcf3de 100644 --- a/lib/node_modules/@stdlib/repl/help/data/data.json +++ b/lib/node_modules/@stdlib/repl/help/data/data.json @@ -1 +1 @@ -{"AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( '{{alias:@stdlib/math/base/special/sin}}' )\n '@stdlib/math/base/special/sin'\n\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( '{{alias:@stdlib/math/base/special/sin}}' )\n [...]\n\n","aliases":"\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n","ARCH":"\nARCH\n Operating system CPU architecture.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new {{alias:@stdlib/array/buffer}}( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n","arrayDataTypes":"\narrayDataTypes()\n Returns a list of array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n \n\n","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Array data type.\n\n dtype2: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups })\n\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( {{alias:@stdlib/constants/math/float64-pinf}}, {{alias:@stdlib/constants/math/float64-ninf}} )\n Infinity\n > d = base.absdiff( {{alias:@stdlib/constants/math/float64-pinf}}, {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n\n","base.absInt32":"\nbase.absInt32( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.absInt32( -1|0 )\n 1\n > v = base.absInt32( 2|0 )\n 2\n > v = base.absInt32( 0|0 )\n 0\n\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent (in radians).\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.0\n > y = base.asin( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( {{alias:@stdlib/constants/math/float64-ninf}} )\n -Infinity\n > y = base.asinh( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -{{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~-1.004\n > y = base.atan( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n","base.atan2":"\nbase.atan2( y, x )\n Evaluates the arctangent of the quotient of two numbers.\n\n Parameters\n ----------\n y: number\n Numerator.\n\n x: number\n Denominator.\n\n Returns\n -------\n out: number\n Arctangent of `y/x` (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.0\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.besselj0( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.besselj1( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.bessely0( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.bessely1( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n","base.cabs":"\nbase.cabs( re, im )\n Computes the absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( 5.0, 3.0 )\n ~5.831\n\n","base.cabs2":"\nbase.cabs2( re, im )\n Computes the squared absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( 5.0, 3.0 )\n 34.0\n\n","base.cadd":"\nbase.cadd( [out,] re1, im1, re2, im2 )\n Adds two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cadd( 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float32}}( 2 );\n > y = base.cadd( out, 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n > var bool = ( y === out )\n true\n\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n","base.cceil":"\nbase.cceil( [out,] re, im )\n Rounds a complex number toward positive infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceil( 5.5, 3.3 )\n [ 6.0, 4.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cceil( out, 5.5, 3.3 )\n [ 6.0, 4.0 ]\n > var bool = ( v === out )\n true\n\n","base.cceiln":"\nbase.cceiln( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward positive\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cceiln( out, 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n > var bool = ( v === out )\n true\n\n","base.ccis":"\nbase.ccis( [out,] re, im )\n Computes the cis function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.ccis( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > var y = base.ccis( 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.ccis( out, 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n","base.cdiv":"\nbase.cdiv( [out,] re1, im1, re2, im2 )\n Divides two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cdiv( -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cdiv( out, -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n","base.ceil":"\nbase.ceil( x )\n Rounds a numeric value toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n","base.ceilsd":"\nbase.ceilsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1 )\n 4.0\n > y = base.ceilsd( 12368.0, 2 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n","base.cexp":"\nbase.cexp( [out,] re, im )\n Computes the exponential function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cexp( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > y = base.cexp( 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cexp( out, 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n","base.cflipsign":"\nbase.cflipsign( [out,] re, im, y )\n Returns a complex number with the same magnitude as `z` and the sign of\n `y*z`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.cflipsign( -4.2, 5.5, -9 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cflipsign( out, -4.2, 5.5, 8 )\n [ -4.2, 5.5 ]\n > var bool = ( v === out )\n true\n\n","base.cfloor":"\nbase.cfloor( [out,] re, im )\n Rounds a complex number toward negative infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cfloor( 5.5, 3.3 )\n [ 5.0, 3.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cfloor( out, 5.5, 3.3 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n","base.cfloorn":"\nbase.cfloorn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward negative\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cfloorn( 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cfloorn( out, 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n > var bool = ( v === out )\n true\n\n","base.cinv":"\nbase.cinv( [out,] re, im )\n Computes the inverse of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cinv( 2.0, 4.0 )\n [ 0.1, -0.2 ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cinv( out, 2.0, 4.0 )\n [ 0.1, -0.2 ]\n > var bool = ( v === out )\n true\n\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a value to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n","base.cmul":"\nbase.cmul( [out,] re1, im1, re2, im2 )\n Multiplies two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.cmul( 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cmul( out, 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n > var bool = ( v === out )\n true\n\n","base.cneg":"\nbase.cneg( [out,] re, im )\n Negates a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Negated components.\n\n Examples\n --------\n > var out = base.cneg( -4.2, 5.5 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cneg( out, -4.2, 5.5 )\n [ 4.2, -5.5 ]\n > var bool = ( v === out )\n true\n\n","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~0.707\n > y = base.cos( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~-0.293\n > y = base.cosm1( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n","base.cphase":"\nbase.cphase( re, im )\n Computes the argument of a complex number in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( 5.0, 3.0 )\n ~0.5404\n\n","base.cpolar":"\nbase.cpolar( [out,] re, im )\n Returns the absolute value and phase of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cpolar( out, 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n","base.cround":"\nbase.cround( [out,] re, im )\n Rounds a complex number to the nearest integer.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cround( 5.5, 3.3 )\n [ 6.0, 3.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.cround( out, 5.5, 3.3 )\n [ 6.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n","base.croundn":"\nbase.croundn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.croundn( 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.croundn( out, 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n > var bool = ( v === out )\n true\n\n","base.csignum":"\nbase.csignum( [out,] re, im )\n Evaluates the signum function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.csignum( -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.csignum( out, -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n > var bool = ( v === out )\n true\n\n","base.csub":"\nbase.csub( [out,] re1, im1, re2, im2 )\n Subtracts two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.csub( 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.csub( out, 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n > var bool = ( v === out )\n true\n\n","base.dasum":"\nbase.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.dasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.dasum( N, x1, stride )\n 12.0\n\n\nbase.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n\nbase.dasum.wasm( [options] )\n Returns a memory managed function to compute the sum of absolute values.\n\n For an externally defined `Float64Array`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.dasum.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var bytes = wasm.malloc( N * 8 );\n\n // Create a Float64Array view:\n > var view = new {{alias:@stdlib/array/float64}}( bytes.buffer, bytes.byteOffset, N );\n\n // Copy data to the heap:\n > view.set( [ 1.0, -2.0, 3.0, -4.0, 5.0 ] );\n\n // Compute the sum of absolute values (passing in the heap buffer):\n > var s = wasm( N, bytes, 1 )\n 15.0\n\n // Free the memory:\n > wasm.free( bytes );\n\n","base.daxpy":"\nbase.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.daxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.daxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.daxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.wasm( [options] )\n Returns a memory managed function to multiply `x` by a constant `alpha` and\n add the result to `y`.\n\n For externally defined `Float64Arrays`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.daxpy.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var xbytes = wasm.malloc( N * 8 );\n > var ybytes = wasm.malloc( N * 8 );\n\n // Create Float64Array views:\n > var x = new {{alias:@stdlib/array/float64}}( xbytes.buffer, xbytes.byteOffset, N );\n > var y = new {{alias:@stdlib/array/float64}}( ybytes.buffer, ybytes.byteOffset, N );\n\n // Copy data to the heap:\n > x.set( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > y.set( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n\n // Multiply and add alpha:\n > var alpha = 5.0;\n > wasm( x.length, alpha, xbytes, 1, ybytes, 1 );\n > y\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Free the memory:\n > wasm.free( xbytes );\n > wasm.free( ybytes );\n\n","base.dcopy":"\nbase.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.dcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.dcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float64}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.dcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of a F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns a F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of a F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of a F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of a F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for a F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for a F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of a F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of a F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of a F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( {{alias:@stdlib/constants/math/float64-pinf}}, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( {{alias:@stdlib/constants/math/float64-ninf}}, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n > y = base.ellipe( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( {{alias:@stdlib/constants/math/float64-pinf}} )\n NaN\n > y = base.ellipk( {{alias:@stdlib/constants/math/float64-ninf}} )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0.0\n > y = base.erfc( {{alias:@stdlib/constants/math/float64-ninf}} )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e34 ) )\n 114\n > exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`, else behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.14, 10.0 )\n -3.14\n > z = base.flipsign( -3.14, -1.0 )\n 3.14\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.14, -0.0 )\n 3.14\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( 4294967295.0 ) )\n -1\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14 ) )\n 3\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n -3\n > y = base.float32ToInt32( {{alias:@stdlib/number/float64/base/to-float32}}( NaN ) )\n 0\n > y = base.float32ToInt32( {{alias:@stdlib/constants/math/float32-pinf}} )\n 0\n > y = base.float32ToInt32( {{alias:@stdlib/constants/math/float32-ninf}} )\n 0\n","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( 4294967297.0 ) )\n 1\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14 ) )\n 3\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( {{alias:@stdlib/number/float64/base/to-float32}}( NaN ) )\n 0\n > y = base.float32ToUint32( {{alias:@stdlib/constants/math/float32-pinf}} )\n 0\n > y = base.float32ToUint32( {{alias:@stdlib/constants/math/float32-ninf}} )\n 0\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0\n > y = base.float64ToInt32( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0\n","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( {{alias:@stdlib/constants/math/float64-pinf}} )\n 0\n > y = base.float64ToUint32( {{alias:@stdlib/constants/math/float64-ninf}} )\n 0\n","base.floor":"\nbase.floor( x )\n Rounds a numeric value toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward negative\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n","base.floorsd":"\nbase.floorsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5 )\n 3.1415\n > y = base.floorsd( 3.14159, 1 )\n 3.0\n > y = base.floorsd( 12368.0, 2 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n","base.fresnel":"\nbase.fresnel( [out,] x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.fresnel( out, 0.0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( {{alias:@stdlib/constants/math/float64-pinf}} )\n ~0.5\n > y = base.fresnelc( {{alias:@stdlib/constants/math/float64-ninf}} )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( {{alias:@stdlib/constants/math/float64-pinf}} )\n ~0.5\n > y = base.fresnels( {{alias:@stdlib/constants/math/float64-ninf}} )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n","base.frexp":"\nbase.frexp( [out,] x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, 0 ]\n > out = base.frexp( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var y = base.frexp( out, 4.0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n","base.fromWordf":"\nbase.fromWordf( x )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n","base.gasum":"\nbase.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.gasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.gasum( N, x1, stride )\n 12.0\n\n\nbase.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > sum = base.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n","base.gaxpy":"\nbase.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gaxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.gaxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gaxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n","base.gcopy":"\nbase.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float64}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.gcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.gcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n","base.imuldw":"\nbase.imuldw( [out,] a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( {{alias:@stdlib/number/float64/base/to-int32}}( -32 ) )\n 4294967264\n > y = base.int32ToUint32( {{alias:@stdlib/number/float64/base/to-int32}}( 3 ) )\n 3\n\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( {{alias:@stdlib/constants/math/float64-pinf}} )\n false\n > bool = base.isFinite( {{alias:@stdlib/constants/math/float64-ninf}} )\n false\n\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( {{alias:@stdlib/constants/math/float64-pinf}} )\n true\n > bool = base.isInfinite( {{alias:@stdlib/constants/math/float64-ninf}} )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a numeric value is a probability.\n\n A probability is defined as a numeric value on the closed interval `[0,1]`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kernelBetainc":"\nbase.kernelBetainc( [out,] x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.32, 1.6 ]\n\n > out = new Array( 2 );\n > var v = base.kernelBetainc( out, 0.2, 1.0, 2.0, true, true )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( {{alias:@stdlib/constants/math/float64-pi}}/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( {{alias:@stdlib/constants/math/float64-pinf}}, 11 )\n Infinity\n > x = base.ldexp( {{alias:@stdlib/constants/math/float64-ninf}}, -118 )\n -Infinity\n\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of `x`.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( {{alias:@stdlib/constants/math/float64-pinf}} )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n","base.max":"\nbase.max( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n","base.maxabs":"\nbase.maxabs( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n","base.min":"\nbase.min( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n","base.minabs":"\nbase.minabs( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n","base.minmax":"\nbase.minmax( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmax( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmax( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n","base.minmaxabs":"\nbase.minmaxabs( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabs( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmaxabs( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n","base.modf":"\nbase.modf( [out,] x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n parts: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, +0.0 ]\n > parts = base.modf( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > parts = base.modf( out, 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n\n","base.ndarray":"\nbase.ndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarray( 'float64', 3 )\n \n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n","base.ndarrayMemoized":"\nbase.ndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarrayMemoized( 'float64', 3 )\n \n > var f = base.ndarrayMemoized( 'float64', 3 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n","base.normalize":"\nbase.normalize( [out,] x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*{{alias:@stdlib/math/base/special/pow}}(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( {{alias:@stdlib/constants/math/float64-pinf}} )\n [ Infinity, 0 ]\n > out = base.normalize( {{alias:@stdlib/constants/math/float64-ninf}} )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.normalize( out, 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > bool = ( v === out )\n true\n\n","base.normalizef":"\nbase.normalizef( [out,] x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( {{alias:@stdlib/number/float64/base/to-float32}}( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*{{alias:@stdlib/math/base/special/pow}}(2,exp) === {{alias:@stdlib/number/float64/base/to-float32}}(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( {{alias:@stdlib/constants/math/float32-pinf}} )\n [ Infinity, 0 ]\n > out = base.normalizef( {{alias:@stdlib/constants/math/float32-ninf}} )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new {{alias:@stdlib/array/float32}}( 2 );\n > var v = base.normalizef( out, {{alias:@stdlib/number/float64/base/to-float32}}( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( {{alias:@stdlib/constants/math/float64-pi}}, 5.0 )\n ~306.0197\n > y = base.pow( {{alias:@stdlib/constants/math/float64-pi}}, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( {{alias:@stdlib/constants/math/float64-pi}}, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n 90.0\n > d = base.rad2deg( -{{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( {{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n 29.999999999999996\n\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[1, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 1\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function\n returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = {{alias:@stdlib/math/base/special/abs}}( x );\n ... y = {{alias:@stdlib/math/base/special/abs}}( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * {{alias:@stdlib/constants/math/float64-eps}};\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = new Array( 2 );\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( y )\n '00000000000000000000011000000000'\n\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = {{alias:@stdlib/number/uint32/base/to-binary-string}}( y )\n '00000000010000000000000000000000'\n\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n","base.sasum":"\nbase.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > var stride = 2;\n > sum = base.sasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > sum = base.sasum( N, x1, stride )\n 12.0\n\n\nbase.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n","base.saxpy":"\nbase.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.saxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.saxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.saxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n","base.scopy":"\nbase.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.scopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );\n > base.scopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new {{alias:@stdlib/array/float32}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new {{alias:@stdlib/array/float32}}( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );\n > base.scopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( {{alias:@stdlib/constants/math/float64-pinf}}, high )\n 1.0\n\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( {{alias:@stdlib/constants/math/float64-pinf}}, low )\n NaN\n > y = base.setLowWord( {{alias:@stdlib/constants/math/float64-ninf}}, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n","base.sici":"\nbase.sici( [out,] x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > y = base.sici( out, 3.0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n\n","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( {{alias:@stdlib/number/float64/base/to-float32}}( 4.0 ) )\n false\n > bool = base.signbitf( {{alias:@stdlib/number/float64/base/to-float32}}( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e34 ) )\n 4293751\n > s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( 3.14e-34 ) )\n 5288021\n > s = base.significandf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n ~1.0\n > y = base.sin( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n","base.sincos":"\nbase.sincos( [out,] x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( {{alias:@stdlib/constants/math/float64-pi}}/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -{{alias:@stdlib/constants/math/float64-pi}}/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.sincos( out, 0.0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n","base.sincospi":"\nbase.sincospi( [out,] x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n > var out = new {{alias:@stdlib/array/float64}}( 2 );\n > var v = base.sincospi( out, 0.0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n","base.spence":"\nbase.spence( x )\n Evaluates Spence’s function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -{{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~-1.0\n > y = base.tan( {{alias:@stdlib/constants/math/float64-pi}}/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-pi}} )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-pinf}} )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( {{alias:@stdlib/constants/math/float64-ninf}} )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( {{alias:@stdlib/constants/math/float64-pi}} ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( {{alias:@stdlib/number/float64/base/to-float32}}( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/constants/math/float32-pinf}} )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( {{alias:@stdlib/constants/math/float32-ninf}} )\n '11111111100000000000000000000000'\n\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint8}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint16}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new {{alias:@stdlib/array/uint32}}( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = {{alias:@stdlib/number/float64/base/to-float32}}( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n","base.toWords":"\nbase.toWords( [out,] x )\n Splits a floating-point number into a higher order word (unsigned 32-bit\n integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n // Provide an output array:\n > var out = new {{alias:@stdlib/array/uint32}}( 2 );\n > w = base.toWords( out, 3.14e201 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n","base.trunc":"\nbase.trunc( x )\n Rounds a numeric value toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n","base.truncsd":"\nbase.truncsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5 )\n 3.1415\n > y = base.truncsd( 3.14159, 1 )\n 3.0\n > y = base.truncsd( 12368.0, 2 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n","base.uimul":"\nbase.uimul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.uimul( 10>>>0, 4>>>0 )\n 40\n\n","base.uimuldw":"\nbase.uimuldw( [out,] a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.uimuldw( 1, 10 )\n [ 0, 10 ]\n\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( {{alias:@stdlib/number/float64/base/to-uint32}}( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( {{alias:@stdlib/number/float64/base/to-uint32}}( 3 ) )\n 3\n\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n The returned JSON object has the following properties:\n\n - type: value type\n - data: buffer data as a generic array\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/buffer/alloc-unsafe}}( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can be expected frequencies, population probabilities\n summing to one, or a discrete probability distribution name to test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: Array\n Observation frequencies.\n\n y: Array|string\n Expected frequencies (or probabilities) or a discrete probability\n distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p )\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.print()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.print()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts )\n {...}\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = {{alias:@stdlib/random/base/poisson}}.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new {{alias:@stdlib/array/int32}}( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda )\n {...}\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n buf.clear: Function\n Clears the buffer.\n\n buf.count: integer\n Number of elements currently in the buffer.\n\n buf.full: boolean\n Boolean indicating whether the buffer is full.\n\n buf.iterator: Function\n Returns an iterator for iterating over a buffer. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that a\n returned iterator does **not** iterate over partially full buffers.\n\n buf.length: integer\n Buffer length (capacity).\n\n buf.push: Function\n Adds a value to the buffer. If the buffer is full, the method returns\n the removed value; otherwise, the method returns `undefined`.\n\n buf.toArray: Function\n Returns an array of buffer values.\n\n buf.toJSON: Function\n Serializes a circular buffer as JSON.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary\n - phones: manners of articulation for each sound\n - symbols: complete list of ARPABET symbols used by the dictionary\n - vp: verbal pronunciations of punctuation marks\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 4.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 8.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 8.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 16.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n","conj":"\nconj( z )\n Returns the complex conjugate of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Complex\n Complex conjugate.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n","contains":"\ncontains( val, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `val` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `val` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does not distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n val: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n The function supports the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n arr: Array|TypedArray\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n The function supports input arrays having the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n x: Array|TypedArray\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new {{alias:@stdlib/array/float32}}( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = {{alias:@stdlib/buffer/from-array}}( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n\n Returns\n -------\n out: Array\n List of familiar English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: bool\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","endsWith":"\nendsWith( str, search[, len] )\n Tests if a `string` ends with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` ends with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: Array\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups })\n\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566601151848\n\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/float64}}( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > {{alias:@stdlib/number/uint32/base/to-binary-string}}( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > {{alias:@stdlib/number/uint32/base/to-binary-string}}( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/float32}}( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n createServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var createServer = httpServer()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > createServer = httpServer( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > createServer = httpServer( opts )\n \n\n\ncreateServer( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var createServer = httpServer();\n > createServer( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object\n - result: either `x` or `y`\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion\n\n The predicate function callback accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n","imag":"\nimag( z )\n Returns the imaginary component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( {{alias:@stdlib/random/base/normal}}( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( {{alias:@stdlib/random/base/normal}}( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var vec = {{alias:@stdlib/ndarray/ctor}}( 'float64', 1 );\n > var buf = new {{alias:@stdlib/array/float64}}( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value\n - w: weight\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n","ind2sub":"\nind2sub( [out,] shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'wrap', the function wraps around\n a linear index exceeding array dimensions using modulo arithmetic. If\n equal to 'clamp', the function sets a linear index exceeding array\n dimensions to either `0` (minimum linear index) or the maximum linear\n index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n // Provide an output array:\n > var out = new Array( d.length );\n > s = ind2sub( out, d, 17 )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int16}}( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new {{alias:@stdlib/array/buffer}}( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( {{alias:@stdlib/string/from-code-point}}( 130 ) )\n false\n\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new {{alias:@stdlib/buffer/ctor}}( 'beep' ) )\n true\n > bool = isBuffer( new {{alias:@stdlib/buffer/ctor}}( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 2, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplex( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new {{alias:@stdlib/array/complex64}}( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new {{alias:@stdlib/array/complex128}}( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new {{alias:@stdlib/complex/float32}}( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new {{alias:@stdlib/complex/float64}}( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new {{alias:@stdlib/array/complex64}}( 10 ) )\n true\n\n","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new {{alias:@stdlib/array/float32}}( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new {{alias:@stdlib/array/float64}}( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new {{alias:@stdlib/array/int16}}( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new {{alias:@stdlib/array/int32}}( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = {{alias:@stdlib/utils/named-typed-tuple}}( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( {{alias:@stdlib/random/base/randu}} )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > {{alias:@stdlib/utils/inherit}}( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new {{alias:@stdlib/array/shared-buffer}}( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 2, 1, -1, -2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 1, 0, 0, -1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, -1, 1, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, 0, 0, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var mat = {{alias:@stdlib/ndarray/ctor}}( 'generic', 2 );\n > var M = mat( [ 0, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new {{alias:@stdlib/array/int8}}( 10 ) )\n true\n\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new {{alias:@stdlib/array/int16}}() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new {{alias:@stdlib/array/uint8}}( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new {{alias:@stdlib/array/uint8c}}( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new {{alias:@stdlib/array/uint16}}( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new {{alias:@stdlib/array/uint32}}( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new {{alias:@stdlib/array/uint8}}( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value\n - index: iterated value index (zero-based)\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( {{alias:@stdlib/random/iter/randu}}( opts ) )\n\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = {{alias:@stdlib/random/iter/randu}}({ 'iter': 10 });\n > var out = new {{alias:@stdlib/array/float64}}( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = {{alias:@stdlib/random/iter/randu}}({ 'iter': 10 });\n > var out = new {{alias:@stdlib/array/float64}}( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = {{alias:@stdlib/random/iter/randu}}( opts );\n > var s = iteratorStream( it );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = {{alias:@stdlib/random/iter/randu}}( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = {{alias:@stdlib/simulate/iter/sine-wave}}();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( {{alias:@stdlib/random/iter/randu}}() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value\n - sprev: previous source iterated value\n - dprev: previous downstream iterated value\n - index: source iteration index (zero-based)\n - acc: previous resolved value\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n","iterFibonacci":"\niterFibonacci( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacci();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( {{alias:@stdlib/random/iter/randu}}(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it1 = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = {{alias:@stdlib/iter/head}};\n > o.some = {{alias:@stdlib/iter/some}};\n > var fiter = iterFlow( o );\n > var it1 = fiter( {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( {{alias:@stdlib/random/iter/randu}}(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( {{alias:@stdlib/random/iter/randu}}(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( {{alias:@stdlib/random/iter/randu}}(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values\n - index: iteration index (zero-based)\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n","iterNonFibonacci":"\niterNonFibonacci( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacci();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/iter/pipeline-thunk}}( {{alias:@stdlib/iter/head}}, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = {{alias:@stdlib/iter/pipeline-thunk}}( {{alias:@stdlib/iter/some-by}}, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( {{alias:@stdlib/random/iter/randu}}() )\n \n\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value\n - index: source iteration index (zero-based)\n - n: iteration index (zero-based)\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( {{alias:@stdlib/random/iter/randu}}(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 5.0 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( {{alias:@stdlib/iter/some}}, 3 );\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = {{alias:@stdlib/array/to-iterator}}( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = {{alias:@stdlib/array/to-iterator}}( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n","kde2d":"","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups })\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 4839 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = {{alias:@stdlib/random/base/uniform}}.factory( 0.0, 1.0, { 'seed': 8798 })\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 })\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = {{alias:@stdlib/random/base/uniform}}.factory( 0.0, 1.0, { 'seed': 8798 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' })\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' })\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true })\n { pValue: ~1, statistic: 0.1, ... }\n\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n","linspace":"\nlinspace( start, stop[, length] )\n Generates a linearly spaced numeric array.\n\n If a `length` is not provided, the default output array length is `100`.\n\n The output array is guaranteed to include the `start` and `stop` values.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Last array value.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = linspace( 0, 100, 6 )\n [ 0, 20, 40, 60, 80, 100 ]\n\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n","lowercase":"\nlowercase( str )\n Converts a `string` to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new {{alias:@stdlib/array/float64}}( 100 );\n > var y = new {{alias:@stdlib/array/float64}}( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*{{alias:@stdlib/random/base/randn}}() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = {{alias:@stdlib/plot/ctor}}( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - `index`: invocation index (starting from zero)\n - `next`: callback to be invoked upon function completion\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `key`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `key`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `key`\n - `value`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `key`: transformed key\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `value`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `value`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `value`\n - `key`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `value`: transformed value\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size\n - cities: cities\n - labels: map labels\n - temperature: temperature during the army's return from Russia\n - rivers: river data\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var river = data.river\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier)\n - title: chapter title (if available; otherwise, empty)\n - text: chapter text\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( {{alias:@stdlib/array/float64}}[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...[, elementN]]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element: number\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n","ndarray":"\nndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarray( 'generic', 2 )\n \n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types\n - 'equiv': allow casting between identical and byte swapped types\n - 'safe': only allow \"safe\" casts\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats)\n - 'unsafe': allow casting between all types (including between integers and\n floats)\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'same-kind', 'unsafe' ]\n\n","ndarrayDataTypes":"\nndarrayDataTypes()\n Returns a list of ndarray data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n \n\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'clamp', 'wrap' ]\n\n","ndarrayMemoized":"\nndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarrayMemoized( 'generic', 2 )\n \n > var f = ndarrayMemoized( 'generic', 2 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n ndarray data type.\n\n dtype2: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son. .\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number\n - town: town name\n - town_id: town identifier\n - tract: tract identifier\n - lon: longitude\n - lat: latitude\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' })\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' })\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n Examples\n --------\n > function done( error ) { if ( error ) { throw error; } };\n > var files = [ './a.js', './b.js' ];\n > parallel( files, done );\n\n // Specify the number of workers:\n > var opts = { 'workers': 8 };\n > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = {{alias:@stdlib/random/base/normal}}( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + {{alias:@stdlib/random/base/normal}}( 0.0,\n ... {{alias:@stdlib/math/base/special/sqrt}}( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","RE_BASENAME":"\nRE_BASENAME\n Regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_BASENAME.posix\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nRE_BASENAME.win32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n","RE_BASENAME_POSIX":"\nRE_BASENAME_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n","RE_BASENAME_WINDOWS":"\nRE_BASENAME_WINDOWS\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n","RE_COLOR_HEXADECIMAL":"\nRE_COLOR_HEXADECIMAL\n Regular expression to match a hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.test( '000' )\n false\n > bool = RE_COLOR_HEXADECIMAL.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.shorthand\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'ffffff' )\n false\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.either\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.either.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( 'beep' )\n false\n\n","RE_DECIMAL_NUMBER":"\nRE_DECIMAL_NUMBER\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var bool = RE_DECIMAL_NUMBER.test( '1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '-1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0' )\n false\n > bool = RE_DECIMAL_NUMBER.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = new RegExp( RE_DECIMAL_NUMBER.source, 'g' );\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\n","RE_DIRNAME":"\nRE_DIRNAME\n Regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_DIRNAME.posix\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nRE_DIRNAME.win32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\\\foo\\\\bar'\n\n","RE_DIRNAME_POSIX":"\nRE_DIRNAME_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( './' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n","RE_DIRNAME_WINDOWS":"\nRE_DIRNAME_WINDOWS\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\\\foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\\\foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n","RE_EOL":"\nRE_EOL\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\n","RE_EXTENDED_LENGTH_PATH":"\nRE_EXTENDED_LENGTH_PATH\n Regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Examples\n --------\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n\n","RE_EXTNAME":"\nRE_EXTNAME\n Regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_EXTNAME.posix\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nRE_EXTNAME.win32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n","RE_EXTNAME_POSIX":"\nRE_EXTNAME_POSIX\n Regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( '.' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( './' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n","RE_EXTNAME_WINDOWS":"\nRE_EXTNAME_WINDOWS\n Regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE_EXTNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n","RE_FILENAME":"\nRE_FILENAME\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_FILENAME.posix\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nRE_FILENAME.win32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n","RE_FILENAME_POSIX":"\nRE_FILENAME_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_POSIX.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_POSIX.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( './' ).slice()\n [ './', '', '.', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n","RE_FILENAME_WINDOWS":"\nRE_FILENAME_WINDOWS\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( './' ).slice()\n [ './', '', '', '.', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n","RE_FUNCTION_NAME":"\nRE_FUNCTION_NAME\n Regular expression to capture a function name.\n\n Examples\n --------\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n","RE_NATIVE_FUNCTION":"\nRE_NATIVE_FUNCTION\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = RE_NATIVE_FUNCTION.test( Date.toString() )\n true\n > bool = RE_NATIVE_FUNCTION.test( (function noop() {}).toString() )\n false\n\n","RE_REGEXP":"\nRE_REGEXP\n Regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Examples\n --------\n > var bool = RE_REGEXP.test( '/^beep$/' )\n true\n > bool = RE_REGEXP.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE_REGEXP.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE_REGEXP.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n","RE_UNC_PATH":"\nRE_UNC_PATH\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '//server/share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = './foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE_UNC_PATH.test( path )\n false\n\n","RE_UTF16_SURROGATE_PAIR":"\nRE_UTF16_SURROGATE_PAIR\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var bool = RE_UTF16_SURROGATE_PAIR.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE_UTF16_SURROGATE_PAIR.test( 'abcdef' )\n false\n\n","RE_UTF16_UNPAIRED_SURROGATE":"\nRE_UTF16_UNPAIRED_SURROGATE\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var bool = RE_UTF16_UNPAIRED_SURROGATE.test( 'abc' )\n false\n > bool = RE_UTF16_UNPAIRED_SURROGATE.test( '\\uD800' )\n true\n\n","RE_WHITESPACE":"\nRE_WHITESPACE\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var bool = RE_WHITESPACE.test( '\\n' )\n true\n > bool = RE_WHITESPACE.test( ' ' )\n true\n > bool = RE_WHITESPACE.test( 'a' )\n false\n\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n","readFile":"\nreadFile( file[, options,] clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n","readFileList":"\nreadFileList( filepaths[, options,] clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path\n - data: file contents as either a Buffer or string\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readJSON":"\nreadJSON( file[, options,] clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n","readWASM":"\nreadWASM( file, [options,] clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n","real":"\nreal( z )\n Returns the real component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n","reduce":"\nreduce( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) { return acc + v; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduce( arr, 0, sum )\n 6.0\n\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n","reduceRight":"\nreduceRight( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) {\n ... console.log( '%s: %d', acc, v );\n ... return acc + v;\n ... };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduceRight( arr, 0, sum );\n 2: 3.0\n 1: 2.0\n 0: 1.0\n > out\n 6.0\n\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reim":"\nreim( z )\n Returns the real and imaginary components of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new {{alias:@stdlib/complex/float64}}( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n","removeFirst":"\nremoveFirst( str )\n Removes the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n\n","removeLast":"\nremoveLast( str )\n Removes the last character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n","replace":"\nreplace( str, search, newval )\n Replaces `search` occurrences with a replacement `string`.\n\n When provided a `string` as the `search` value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","resolveParentPath":"\nresolveParentPath( path[, options,] clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n","reverseString":"\nreverseString( str )\n Reverses a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( {{alias:@stdlib/random/base/mt19937}} );\n > var r = {{alias:@stdlib/utils/parse-json}}( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer)\n - data: buffer data as an array of integers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = {{alias:@stdlib/utils/parse-json}}( str, reviveBuffer )\n [ 5, 3 ]\n\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\")\n - re: real component (number)\n - im: imaginary component (number)\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex )\n \n\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex64 )\n \n\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = {{alias:@stdlib/utils/parse-json}}( str, reviveComplex128 )\n \n\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\")\n - data: typed array data as an array of numbers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = {{alias:@stdlib/utils/parse-json}}( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 })\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 })\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 })\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false })\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs })\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false })\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 });\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 });\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > {{alias:@stdlib/utils/keys}}( obj )\n []\n\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' });\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' });\n > bool = ( arr === out )\n false\n\n","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - complex128: 128-bit complex numbers\n - complex64: 64-bit complex numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year\n - name: President name\n - party: the President's political party\n - text: speech text\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group)\n - group: message group\n - checksum: object containing checksum info\n - text: message text (including headers)\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages)\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages)\n - hard-ham-1: harder to detect non-spam e-mails (250 messages)\n - spam-1: spam e-mails (500 messages)\n - spam-2: spam e-mails collected at a later date (1396 messages)\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5)\n - value: checksum value\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a `string` starts with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` starts with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = {{alias:@stdlib/streams/node/inspect-sink}}.objectMode( fcn );\n > s.pipe( o );\n\n","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'wrap', the function wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` options is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = {{alias:@stdlib/time/tic}}();\n > var delta = toc( start )\n [ , ]\n\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( {{alias:@stdlib/random/base/randu}}() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - result: function result\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object\n - result: either the result of `x` or the provided argument `y`\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( {{alias:@stdlib/random/base/randu}}() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory( 0.0, 2.0, { 'seed': 5776 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = {{alias:@stdlib/random/base/normal}}.factory( 1.0, 2.0, { 'seed': 786 });\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' });\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' })\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type\n - data: typed array data as a generic array\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new {{alias:@stdlib/array/float64}}( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n","typedarrayComplexCtors":"\ntypedarrayComplexCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayComplexCtors( 'complex64' )\n \n > ctor = typedarrayComplexCtors( 'float32' )\n null\n\n","typedarrayComplexDataTypes":"\ntypedarrayComplexDataTypes()\n Returns a list of complex typed array data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = typedarrayComplexDataTypes()\n \n\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new {{alias:@stdlib/array/int8}}( 10 ) )\n 'int8array'\n > t = typeOf( new {{alias:@stdlib/array/uint8}}( 10 ) )\n 'uint8array'\n > t = typeOf( new {{alias:@stdlib/array/uint8c}}( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new {{alias:@stdlib/array/int16}}( 10 ) )\n 'int16array'\n > t = typeOf( new {{alias:@stdlib/array/uint16}}( 10 ) )\n 'uint16array'\n > t = typeOf( new {{alias:@stdlib/array/int32}}( 10 ) )\n 'int32array'\n > t = typeOf( new {{alias:@stdlib/array/uint32}}( 10 ) )\n 'uint32array'\n > t = typeOf( new {{alias:@stdlib/array/float32}}( 10 ) )\n 'float32array'\n > t = typeOf( new {{alias:@stdlib/array/float64}}( 10 ) )\n 'float64array'\n > t = typeOf( new {{alias:@stdlib/array/buffer}}( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new {{alias:@stdlib/buffer/ctor}}( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new {{alias:@stdlib/array/int32}}( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new {{alias:@stdlib/array/buffer}}( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - `+`: enable\n - `-`: disable\n - `=`: enable specified and disable unspecified permissions\n\n For example,\n\n - `u-w`: disable user write permissions\n - `u+w`: enable user write permissions\n - `u=w`: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n","uppercase":"\nuppercase( str )\n Converts a `string` to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > {{alias:@stdlib/utils/define-property}}( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( {{alias:@stdlib/symbol/ctor}} ) ? {{alias:@stdlib/symbol/ctor}}( 'beep' ) : 'beep';\n > {{alias:@stdlib/utils/define-property}}( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n","writeFile":"\nwriteFile( file, data[, options,] clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory( 0.0, 2.0, { 'seed': 212 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 });\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' })\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' })\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = {{alias:@stdlib/random/base/normal}}.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 })\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n"} \ No newline at end of file +{"AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","aliases":"\naliases()\n Returns a list of standard library aliases.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatmentDf: number\n Treatment degrees of freedom.\n\n out.treatmentSS: number\n Treatment sum of squares.\n\n out.treatmentMSS: number\n Treatment mean sum of squares.\n\n out.errorDf: number\n Error degrees of freedom.\n\n out.errorSS: number\n Error sum of squares.\n\n out.errorMSS: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n","ARCH":"\nARCH\n Operating system CPU architecture.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes()\n Returns a list of array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n \n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Array data type.\n\n dtype2: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups })\n\n See Also\n --------\n vartest\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n","base.absInt32":"\nbase.absInt32( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.absInt32( -1|0 )\n 1\n > v = base.absInt32( 2|0 )\n 2\n > v = base.absInt32( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent (in radians).\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( -1.5 )\n ~-0.5236\n > y = base.acovercos( -0.0 )\n ~1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( PI/2.0 )\n ~1.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n Evaluates the arctangent of the quotient of two numbers.\n\n Parameters\n ----------\n y: number\n Numerator.\n\n x: number\n Denominator.\n\n Returns\n -------\n out: number\n Arctangent of `y/x` (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.0\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( re, im )\n Computes the absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( 5.0, 3.0 )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( re, im )\n Computes the squared absolute value of a complex number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( 5.0, 3.0 )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n","base.cadd":"\nbase.cadd( [out,] re1, im1, re2, im2 )\n Adds two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cadd( 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n\n // Provide an output array:\n > var out = new Float32Array( 2 );\n > y = base.cadd( out, 5.0, 3.0, -2.0, 1.0 )\n [ 3.0, 4.0 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n","base.cceil":"\nbase.cceil( [out,] re, im )\n Rounds a complex number toward positive infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceil( 5.5, 3.3 )\n [ 6.0, 4.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cceil( out, 5.5, 3.3 )\n [ 6.0, 4.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n","base.cceiln":"\nbase.cceiln( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward positive\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cceiln( out, 5.555, -3.333, -2 )\n [ 5.56, -3.33 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( [out,] re, im )\n Computes the cis function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.ccis( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > var y = base.ccis( 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.ccis( out, 1.0, 0.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n","base.cdiv":"\nbase.cdiv( [out,] re1, im1, re2, im2 )\n Divides two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cdiv( -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.cdiv( out, -13.0, -1.0, -2.0, 1.0 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cadd, base.cmul, base.csub\n","base.ceil":"\nbase.ceil( x )\n Rounds a numeric value toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1 )\n 4.0\n > y = base.ceilsd( 12368.0, 2 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( [out,] re, im )\n Computes the exponential function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cexp( 0.0, 0.0 )\n [ 1.0, 0.0 ]\n\n > y = base.cexp( 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.cexp( out, 0.0, 1.0 )\n [ ~0.540, ~0.841 ]\n > var bool = ( v === out )\n true\n\n","base.cflipsign":"\nbase.cflipsign( [out,] re, im, y )\n Returns a complex number with the same magnitude as `z` and the sign of\n `y*z`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.cflipsign( -4.2, 5.5, -9 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cflipsign( out, -4.2, 5.5, 8 )\n [ -4.2, 5.5 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cneg, base.csignum\n","base.cfloor":"\nbase.cfloor( [out,] re, im )\n Rounds a complex number toward negative infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cfloor( 5.5, 3.3 )\n [ 5.0, 3.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cfloor( out, 5.5, 3.3 )\n [ 5.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n` toward negative\n infinity.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cfloorn( 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cfloorn( out, 5.555, -3.333, -2 )\n [ 5.55, -3.34 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n","base.cinv":"\nbase.cinv( [out,] re, im )\n Computes the inverse of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var y = base.cinv( 2.0, 4.0 )\n [ 0.1, -0.2 ]\n\n > var out = new Float64Array( 2 );\n > var v = base.cinv( out, 2.0, 4.0 )\n [ 0.1, -0.2 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cdiv\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a value to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.wrap\n","base.cmul":"\nbase.cmul( [out,] re1, im1, re2, im2 )\n Multiplies two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.cmul( 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n\n // Provide an output array:\n > var out = new Float64Array( 2 );\n > var v = base.cmul( out, 5.0, 3.0, -2.0, 1.0 )\n [ -13.0, -1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n","base.cneg":"\nbase.cneg( [out,] re, im )\n Negates a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Negated components.\n\n Examples\n --------\n > var out = base.cneg( -4.2, 5.5 )\n [ 4.2, -5.5 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cneg( out, -4.2, 5.5 )\n [ 4.2, -5.5 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs\n","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n","base.cphase":"\nbase.cphase( re, im )\n Computes the argument of a complex number in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( 5.0, 3.0 )\n ~0.5404\n\n See Also\n --------\n base.cabs\n","base.cpolar":"\nbase.cpolar( [out,] re, im )\n Returns the absolute value and phase of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cpolar( out, 5.0, 3.0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase\n","base.cround":"\nbase.cround( [out,] re, im )\n Rounds a complex number to the nearest integer.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Rounded components.\n\n Examples\n --------\n > var out = base.cround( 5.5, 3.3 )\n [ 6.0, 3.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.cround( out, 5.5, 3.3 )\n [ 6.0, 3.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( [out,] re, im, n )\n Rounds a complex number to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.croundn( 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.croundn( out, 5.555, -3.336, -2 )\n [ 5.56, -3.34 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n","base.csignum":"\nbase.csignum( [out,] re, im )\n Evaluates the signum function of a complex number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re: number\n Real component.\n\n im: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Function result.\n\n Examples\n --------\n > var out = base.csignum( -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.csignum( out, -4.2, 5.5 )\n [ -0.6069136033622302, 0.79476781392673 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.signum\n","base.csub":"\nbase.csub( [out,] re1, im1, re2, im2 )\n Subtracts two complex numbers.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n re1: number\n Real component.\n\n im1: number\n Imaginary component.\n\n re2: number\n Real component.\n\n im2: number\n Imaginary component.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array containing the real and imaginary components of the result.\n\n Examples\n --------\n > var out = base.csub( 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.csub( out, 5.0, 3.0, -2.0, 1.0 )\n [ 7.0, 2.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n","base.dasum":"\nbase.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > sum = base.dasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > sum = base.dasum( N, x1, stride )\n 12.0\n\n\nbase.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.dasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n\nbase.dasum.wasm( [options] )\n Returns a memory managed function to compute the sum of absolute values.\n\n For an externally defined `Float64Array`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.dasum.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var bytes = wasm.malloc( N * 8 );\n\n // Create a Float64Array view:\n > var view = new Float64Array( bytes.buffer, bytes.byteOffset, N );\n\n // Copy data to the heap:\n > view.set( [ 1.0, -2.0, 3.0, -4.0, 5.0 ] );\n\n // Compute the sum of absolute values (passing in the heap buffer):\n > var s = wasm( N, bytes, 1 )\n 15.0\n\n // Free the memory:\n > wasm.free( bytes );\n\n See Also\n --------\n base.daxpy, base.dcopy\n","base.daxpy":"\nbase.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.daxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.daxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.daxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.daxpy.wasm( [options] )\n Returns a memory managed function to multiply `x` by a constant `alpha` and\n add the result to `y`.\n\n For externally defined `Float64Arrays`, data must be copied to the heap.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.memory: integer (optional)\n Total memory. If not provided a buffer, setting the memory option\n instructs the returned function to allocate an internal memory store of\n the specified size.\n\n options.stack: integer (optional)\n Total stack size. Must be less than the memory option and large enough\n for a program's needs. Default: `1024` bytes.\n\n options.buffer: ArrayBuffer (optional)\n `ArrayBuffer` serving as the underlying memory store. If not provided,\n each returned function will allocate and manage its own memory. If\n provided a memory option, the buffer `byteLength` must equal the\n specified total memory.\n\n Returns\n -------\n out: Function\n Memory managed function.\n\n Examples\n --------\n > var wasm = base.daxpy.wasm();\n > var N = 5;\n\n // Allocate space on the heap:\n > var xbytes = wasm.malloc( N * 8 );\n > var ybytes = wasm.malloc( N * 8 );\n\n // Create Float64Array views:\n > var x = new Float64Array( xbytes.buffer, xbytes.byteOffset, N );\n > var y = new Float64Array( ybytes.buffer, ybytes.byteOffset, N );\n\n // Copy data to the heap:\n > x.set( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > y.set( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n\n // Multiply and add alpha:\n > var alpha = 5.0;\n > wasm( x.length, alpha, xbytes, 1, ybytes, 1 );\n > y\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Free the memory:\n > wasm.free( xbytes );\n > wasm.free( ybytes );\n\n See Also\n --------\n base.dasum, base.dcopy\n","base.dcopy":"\nbase.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.dcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.dcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.dcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.dasum, base.daxpy\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.trigamma, base.gamma\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for an\n arcsine distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of a F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns a F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of a F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of a F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of a F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for a F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n a F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for a F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of a F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of a F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of a F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of a F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the logarithm of the probability density function (PDF) for a\n Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n gamma distribution with shape parameter `α` and rate parameter `β` at a\n value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the logarithm of the probability density function (PDF) for a\n Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n Laplace distribution with scale parameter `b` and location parameter `μ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the entropy of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Lévy distribution with location parameter `μ` and scale parameter `c` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the logarithm of the probability density function (PDF) for a Lévy\n distribution with location parameter `μ` and scale parameter `c` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the entropy of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the logarithm of the probability density function (PDF) for a\n logistic distribution with location parameter `μ` and scale parameter `s` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the logarithm of the probability density function (PDF) for a\n Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative probability for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the logarithm of the probability density function (PDF) for a\n uniform distribution with minimum support `a` and maximum support `b` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -infinity\n\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the logarithm of the cumulative distribution function (CDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the logarithm of the probability density function (PDF) for a\n Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipk\n","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv\n","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var polyval = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = polyval( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = polyval( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var rational = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = rational( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = rational( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n See Also\n --------\n base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`, else behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.14, 10.0 )\n -3.14\n > z = base.flipsign( -3.14, -1.0 )\n 3.14\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.14, -0.0 )\n 3.14\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n -1\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 1\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32","base.floor":"\nbase.floor( x )\n Rounds a numeric value toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward negative\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5 )\n 3.1415\n > y = base.floorsd( 3.14159, 1 )\n 3.0\n > y = base.floorsd( 12368.0, 2 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.fresnel":"\nbase.fresnel( [out,] x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n > var out = new Float64Array( 2 );\n > var v = base.fresnel( out, 0.0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels\n","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( [out,] x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var y = base.frexp( out, 4.0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromWordf":"\nbase.fromWordf( x )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n","base.gasum":"\nbase.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > sum = base.gasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > sum = base.gasum( N, x1, stride )\n 12.0\n\n\nbase.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var sum = base.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > sum = base.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.dasum, base.sasum\n","base.gaxpy":"\nbase.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > base.gaxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.gaxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > var alpha = 5.0;\n > base.gaxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = base.floor( x.length / 2 );\n > base.gaxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.daxpy, base.saxpy\n","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n","base.gcopy":"\nbase.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = base.floor( x.length / 2 );\n > base.gcopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.gcopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > var N = base.floor( x.length / 2 );\n > base.gcopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.dcopy\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw, base.uimul\n","base.imuldw":"\nbase.imuldw( [out,] a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n See Also\n --------\n base.imul, base.uimuldw\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a numeric value is a probability.\n\n A probability is defined as a numeric value on the closed interval `[0,1]`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kernelBetainc":"\nbase.kernelBetainc( [out,] x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.32, 1.6 ]\n\n > out = new Array( 2 );\n > var v = base.kernelBetainc( out, 0.2, 1.0, 2.0, true, true )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a number on `[-π/4, π/4]`.\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of `x`.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n","base.max":"\nbase.max( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n","base.maxabs":"\nbase.maxabs( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n","base.min":"\nbase.min( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs\n","base.minabs":"\nbase.minabs( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n","base.minmax":"\nbase.minmax( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmax( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmax( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs\n","base.minmaxabs":"\nbase.minmaxabs( [out,] x[, y[, ...args]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output object.\n\n x: number\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabs( 3.14 )\n [ 3.14, 3.14 ]\n > var out = new Array( 2 );\n > v = base.minmaxabs( out, 3.14 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n","base.modf":"\nbase.modf( [out,] x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n parts: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new Float64Array( 2 );\n > parts = base.modf( out, 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n\n","base.ndarray":"\nbase.ndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarray( 'float64', 3 )\n \n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n See Also\n --------\n array, ndarray\n","base.ndarrayMemoized":"\nbase.ndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = base.ndarrayMemoized( 'float64', 3 )\n \n > var f = base.ndarrayMemoized( 'float64', 3 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n See Also\n --------\n array, base.ndarray, ndarray, ndarrayMemoized\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.normalize":"\nbase.normalize( [out,] x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new Float64Array( 2 );\n > var v = base.normalize( out, 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n","base.normalizef":"\nbase.normalizef( [out,] x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n // Provide an output array:\n > out = new Float32Array( 2 );\n > var v = base.normalizef( out, base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.normhermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.beta\n","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.binomial\n","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[1, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 1\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstd, base.random.randi\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.improvedZiggurat, base.random.randu\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.discreteUniform, base.random.randn\n","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function\n returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n base.random.discreteUniform, base.random.randu\n","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = new Array( 2 );\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a numeric value to the nearest number with `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.sasum":"\nbase.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > sum = base.sasum( N, x, stride )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > sum = base.sasum( N, x1, stride )\n 12.0\n\n\nbase.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of elements to sum.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\n > var sum = base.sasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > sum = base.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.dasum\n","base.saxpy":"\nbase.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > base.saxpy( N, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.saxpy( N, 5.0, x1, -2, y1, 1 )\n [ 40.0, 33.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.saxpy.ndarray( N, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.daxpy\n","base.scopy":"\nbase.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and `stride` parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.scopy( N, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > N = base.floor( x0.length / 2 );\n > base.scopy( N, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y`, with alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of values to copy.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.scopy.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.dcopy\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( [out,] x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Input value.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n // Provide an output array:\n > var out = new Float64Array( 2 );\n > y = base.sici( out, 3.0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n\n","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.sincos":"\nbase.sincos( [out,] x )\n Simultaneously computes the sine and cosine of a number.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n > var out = new Float64Array( 2 );\n > var v = base.sincos( out, 0.0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi\n","base.sincospi":"\nbase.sincospi( [out,] x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Destination array.\n\n x: number\n Input value.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n > var out = new Float64Array( 2 );\n > var v = base.sincospi( out, 0.0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi\n","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.spence":"\nbase.spence( x )\n Evaluates Spence’s function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( [out,] x )\n Splits a floating-point number into a higher order word (unsigned 32-bit\n integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n // Provide an output array:\n > var out = new Uint32Array( 2 );\n > w = base.toWords( out, 3.14e201 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n","base.trunc":"\nbase.trunc( x )\n Rounds a numeric value toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n[, b] )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5 )\n 3.1415\n > y = base.truncsd( 3.14159, 1 )\n 3.0\n > y = base.truncsd( 12368.0, 2 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uimul":"\nbase.uimul( a, b )\n Performs C-like multiplication of two unsigned 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.uimul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n","base.uimuldw":"\nbase.uimuldw( [out,] a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n out: ArrayLikeObject (optional)\n The output array.\n\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: ArrayLikeObject\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.uimuldw( 1, 10 )\n [ 0, 10 ]\n\n See Also\n --------\n base.imuldw, base.uimul\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value on the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n The returned JSON object has the following properties:\n\n - type: value type\n - data: buffer data as a generic array\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can be expected frequencies, population probabilities\n summing to one, or a discrete probability distribution name to test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: Array\n Observation frequencies.\n\n y: Array|string\n Expected frequencies (or probabilities) or a discrete probability\n distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p )\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.print()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.print()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts )\n {...}\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda )\n {...}\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n buf.clear: Function\n Clears the buffer.\n\n buf.count: integer\n Number of elements currently in the buffer.\n\n buf.full: boolean\n Boolean indicating whether the buffer is full.\n\n buf.iterator: Function\n Returns an iterator for iterating over a buffer. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that a\n returned iterator does **not** iterate over partially full buffers.\n\n buf.length: integer\n Buffer length (capacity).\n\n buf.push: Function\n Adds a value to the buffer. If the buffer is full, the method returns\n the removed value; otherwise, the method returns `undefined`.\n\n buf.toArray: Function\n Returns an array of buffer values.\n\n buf.toJSON: Function\n Serializes a circular buffer as JSON.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n See Also\n --------\n FIFO, Stack\n","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary\n - phones: manners of articulation for each sound\n - symbols: complete list of ARPABET symbols used by the dictionary\n - vp: verbal pronunciations of punctuation marks\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 4.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 8.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n See Also\n --------\n complex, Complex128\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n z.BYTES_PER_ELEMENT\n Size (in bytes) of each component. Value: 8.\n\n z.byteLength\n Length (in bytes) of a complex number. Value: 16.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n See Also\n --------\n complex, Complex64\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n","conj":"\nconj( z )\n Returns the complex conjugate of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Complex\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n","contains":"\ncontains( val, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `val` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `val` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does not distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n val: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n The function supports the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n arr: Array|TypedArray\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n The function supports input arrays having the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n x: Array|TypedArray\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar English words.\n\n Returns\n -------\n out: Array\n List of familiar English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: bool\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n > obj\n { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default: undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from one)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n","endsWith":"\nendsWith( str, search[, len] )\n Tests if a `string` ends with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` ends with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: Array\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: Array\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups })\n\n See Also\n --------\n bartlettTest\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566601151848\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn );\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n [ 1.0, 0.0, -1.0 ]\n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - `value`: object property value\n - `key`: object property\n - `obj`: the input object\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: object value\n - `key`: object key\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n createServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var createServer = httpServer()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > createServer = httpServer( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > createServer = httpServer( opts )\n \n\n\ncreateServer( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var createServer = httpServer();\n > createServer( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object\n - result: either `x` or `y`\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion\n\n The predicate function callback accepts two arguments:\n\n - error: error object\n - bool: condition used to determine whether to invoke `x` or `y`\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n","imag":"\nimag( z )\n Returns the imaginary component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium ostrowskianum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var vec = ndarray( 'float64', 1 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = vec( buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value\n - w: weight\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( [out,] shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n out: Array|TypedArray|Object (optional)\n Output array.\n\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'wrap', the function wraps around\n a linear index exceeding array dimensions using modulo arithmetic. If\n equal to 'clamp', the function sets a linear index exceeding array\n dimensions to either `0` (minimum linear index) or the maximum linear\n index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n // Provide an output array:\n > var out = new Array( d.length );\n > s = ind2sub( out, d, 17 )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - `value`\n - `next`\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: value used to update the collection\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 2, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n Parameters\n ----------\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 1, 2, 3, 1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 2, 1, -1, -2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 1, 0, 0, -1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 0, -1, 1, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 0, 0, 0, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var mat = ndarray( 'generic', 2 );\n > var M = mat( [ 0, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n RE_WHITESPACE\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value\n - index: iterated value index (zero-based)\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: destination index (zero-based)\n - n: iteration index (zero-based)\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value\n - sprev: previous source iterated value\n - dprev: previous downstream iterated value\n - index: source iteration index (zero-based)\n - acc: previous resolved value\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterFibonacci":"\niterFibonacci( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacci();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterNonFibonacci\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values\n - index: iteration index (zero-based)\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacci":"\niterNonFibonacci( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacci();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacci\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index (zero-based)\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value\n - index: source iteration index (zero-based)\n - n: iteration index (zero-based)\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value\n - index: iteration index\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n","kde2d":"","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups })\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 })\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 })\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' })\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' })\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true })\n { pValue: ~1, statistic: 0.1, ... }\n\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop[, length] )\n Generates a linearly spaced numeric array.\n\n If a `length` is not provided, the default output array length is `100`.\n\n The output array is guaranteed to include the `start` and `stop` values.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Last array value.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = linspace( 0, 100, 6 )\n [ 0, 20, 40, 60, 80, 100 ]\n\n See Also\n --------\n incrspace, logspace\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n","lowercase":"\nlowercase( str )\n Converts a `string` to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n trim, rtrim\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - `index`: invocation index (starting from zero)\n - `next`: callback to be invoked upon function completion\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `result`: function result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `key`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `key`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `key`\n - `value`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `key`: transformed key\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - `value`: object value corresponding to `key`\n - `key`: object key\n - `obj`: the input object\n - `next`: a callback to be invoked after processing an object `value`\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - `value`\n - `next`\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - `value`\n - `key`\n - `next`\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `value`: transformed value\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size\n - cities: cities\n - labels: map labels\n - temperature: temperature during the army's return from Russia\n - rivers: river data\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var river = data.river\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier)\n - title: chapter title (if available; otherwise, empty)\n - text: chapter text\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( Float64Array[ 1.0, -1.0 ] );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...[, elementN]]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element: number\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p.x\n 1.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the function is unable to resolve indices to a non-empty tuple\n subsequence, the function returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray|null\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n '1,-1,0'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n","ndarray":"\nndarray( dtype, ndims[, options] )\n Returns an ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarray( 'generic', 2 )\n \n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types\n - 'equiv': allow casting between identical and byte swapped types\n - 'safe': only allow \"safe\" casts\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats)\n - 'unsafe': allow casting between all types (including between integers and\n floats)\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayDataTypes":"\nndarrayDataTypes()\n Returns a list of ndarray data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayMemoized":"\nndarrayMemoized( dtype, ndims[, options] )\n Returns a memoized ndarray constructor.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n ndims: integer\n Number of dimensions.\n\n options: Object (optional)\n Options.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n fewer than the number of dimensions, the function recycles modes using\n modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n ctor: Function\n Memoized ndarray constructor.\n\n ctor.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.dtype: string\n Underlying data type.\n\n ctor.ndims: integer\n Number of dimensions.\n\n ctor.prototype.byteLength: integer\n Size (in bytes) of the array (if known).\n\n ctor.prototype.BYTES_PER_ELEMENT: integer\n Size (in bytes) of each array element (if known).\n\n ctor.prototype.data: ArrayLikeObject|TypedArray|Buffer\n Pointer to the underlying data buffer.\n\n ctor.prototype.dtype: string\n Underlying data type.\n\n ctor.prototype.flags: Object\n Information about the memory layout of the array.\n\n ctor.prototype.length: integer\n Length of the array (i.e., number of elements).\n\n ctor.prototype.ndims: integer\n Number of dimensions.\n\n ctor.prototype.offset: integer\n Index offset which specifies the buffer index at which to start\n iterating over array elements.\n\n ctor.prototype.order: string\n Array order. The array order is either row-major (C-style) or column-\n major (Fortran-style).\n\n ctor.prototype.shape: Array\n Array shape.\n\n ctor.prototype.strides: Array\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n ctor.prototype.get: Function\n Returns an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iget: Function\n Returns an array element located at a specified linear index.\n\n ctor.prototype.set: Function\n Sets an array element specified according to provided subscripts. The\n number of provided subscripts should equal the number of dimensions.\n\n ctor.prototype.iset: Function\n Sets an array element located at a specified linear index.\n\n ctor.prototype.toString: Function\n Serializes an ndarray as a string. This method does **not** serialize\n data outside of the buffer region defined by the array configuration.\n\n ctor.prototype.toJSON: Function\n Serializes an ndarray as a JSON object. This method does **not**\n serialize data outside of the buffer region defined by the array\n configuration.\n\n Examples\n --------\n > var ctor = ndarrayMemoized( 'generic', 2 )\n \n > var f = ndarrayMemoized( 'generic', 2 )\n \n > var bool = ( f === ctor )\n true\n\n // To create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ctor( b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n array, ndarray\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n real numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n ndarray data type.\n\n dtype2: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n ndarray data type.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son. .\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - `key`: object key\n - `value`: object value corresponding to `key`\n - `obj`: the input object\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, objectValues\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number\n - town: town name\n - town_id: town identifier\n - tract: tract identifier\n - lon: longitude\n - lat: latitude\n - medv: median value of owner-occupied homes in $1000's\n - cmedv: corrected median value of owner-occupied homes in $1000's\n - crim: per capita crime rate by town\n - zn: proportion of residential land zoned for lots over 25,000 square feet\n - indus: proportion of non-retail business acres per town\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise)\n - nox: nitric oxides concentration (parts per 10 million)\n - rm: average number of rooms per dwelling\n - age: proportion of owner-occupied units built prior to 1940\n - dis: weighted distances to five Boston employment centers\n - rad: index of accessibility to radial highways\n - tax: full-value property-tax rate per $10,000\n - ptratio: pupil-teacher ratio by town\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' })\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' })\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n Examples\n --------\n > function done( error ) { if ( error ) { throw error; } };\n > var files = [ './a.js', './b.js' ];\n > parallel( files, done );\n\n // Specify the number of workers:\n > var opts = { 'workers': 8 };\n > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if prototype successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","RE_BASENAME":"\nRE_BASENAME\n Regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_BASENAME.posix\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nRE_BASENAME.win32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n RE_BASENAME_POSIX, RE_BASENAME_WINDOWS\n","RE_BASENAME_POSIX":"\nRE_BASENAME_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_BASENAME, RE_BASENAME_WINDOWS\n","RE_BASENAME_WINDOWS":"\nRE_BASENAME_WINDOWS\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_BASENAME, RE_BASENAME_POSIX\n","RE_COLOR_HEXADECIMAL":"\nRE_COLOR_HEXADECIMAL\n Regular expression to match a hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.test( '000' )\n false\n > bool = RE_COLOR_HEXADECIMAL.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.shorthand\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'ffffff' )\n false\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.shorthand.test( 'beep' )\n false\n\n\nRE_COLOR_HEXADECIMAL.either\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = RE_COLOR_HEXADECIMAL.either.test( 'ffffff' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( '000' )\n true\n > bool = RE_COLOR_HEXADECIMAL.either.test( 'beep' )\n false\n\n","RE_DECIMAL_NUMBER":"\nRE_DECIMAL_NUMBER\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var bool = RE_DECIMAL_NUMBER.test( '1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '-1.234' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '.0' )\n true\n > bool = RE_DECIMAL_NUMBER.test( '0' )\n false\n > bool = RE_DECIMAL_NUMBER.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = new RegExp( RE_DECIMAL_NUMBER.source, 'g' );\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\n","RE_DIRNAME":"\nRE_DIRNAME\n Regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_DIRNAME.posix\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nRE_DIRNAME.win32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\\\foo\\\\bar'\n\n See Also\n --------\n RE_DIRNAME_POSIX, RE_DIRNAME_WINDOWS, dirname\n","RE_DIRNAME_POSIX":"\nRE_DIRNAME_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE_DIRNAME_POSIX.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( './' )[ 1 ]\n '.'\n > dir = RE_DIRNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_DIRNAME, RE_DIRNAME_WINDOWS, dirname\n","RE_DIRNAME_WINDOWS":"\nRE_DIRNAME_WINDOWS\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\\\foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE_DIRNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\\\foo\\\\bar'\n > dir = RE_DIRNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE_DIRNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_DIRNAME, RE_DIRNAME_POSIX, dirname\n","RE_EOL":"\nRE_EOL\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\n","RE_EXTENDED_LENGTH_PATH":"\nRE_EXTENDED_LENGTH_PATH\n Regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Examples\n --------\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_EXTENDED_LENGTH_PATH.test( path )\n false\n\n","RE_EXTNAME":"\nRE_EXTNAME\n Regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_EXTNAME.posix\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nRE_EXTNAME.win32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var dir = RE_EXTNAME.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n RE_EXTNAME_POSIX, RE_EXTNAME_WINDOWS, extname\n","RE_EXTNAME_POSIX":"\nRE_EXTNAME_POSIX\n Regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_POSIX.exec( '.' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( './' )[ 1 ]\n ''\n > ext = RE_EXTNAME_POSIX.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_EXTNAME, RE_EXTNAME_WINDOWS, extname\n","RE_EXTNAME_WINDOWS":"\nRE_EXTNAME_WINDOWS\n Regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var ext = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE_EXTNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE_EXTNAME_WINDOWS.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE_EXTNAME_WINDOWS.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE_EXTNAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n See Also\n --------\n RE_EXTNAME, RE_EXTNAME_POSIX, extname\n","RE_FILENAME":"\nRE_FILENAME\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.win32`; otherwise,\n `*.posix`.\n\n\nRE_FILENAME.posix\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nRE_FILENAME.win32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = RE_FILENAME.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n RE_FILENAME_POSIX, RE_FILENAME_WINDOWS\n","RE_FILENAME_POSIX":"\nRE_FILENAME_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_POSIX.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_POSIX.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE_FILENAME_POSIX.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_POSIX.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( './' ).slice()\n [ './', '', '.', '.', '' ]\n > parts = RE_FILENAME_POSIX.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n See Also\n --------\n RE_FILENAME, RE_FILENAME_WINDOWS\n","RE_FILENAME_WINDOWS":"\nRE_FILENAME_WINDOWS\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Examples\n --------\n > var parts = RE_FILENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE_FILENAME_WINDOWS.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( './' ).slice()\n [ './', '', '', '.', '.', '' ]\n > parts = RE_FILENAME_WINDOWS.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n See Also\n --------\n RE_FILENAME, RE_FILENAME_POSIX\n","RE_FUNCTION_NAME":"\nRE_FUNCTION_NAME\n Regular expression to capture a function name.\n\n Examples\n --------\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n See Also\n --------\n functionName\n","RE_NATIVE_FUNCTION":"\nRE_NATIVE_FUNCTION\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = RE_NATIVE_FUNCTION.test( Date.toString() )\n true\n > bool = RE_NATIVE_FUNCTION.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n RE_FUNCTION_NAME, functionName\n","RE_REGEXP":"\nRE_REGEXP\n Regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Examples\n --------\n > var bool = RE_REGEXP.test( '/^beep$/' )\n true\n > bool = RE_REGEXP.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE_REGEXP.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE_REGEXP.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n See Also\n --------\n reFromString\n","RE_UNC_PATH":"\nRE_UNC_PATH\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '//server/share';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = 'foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = './foo/bar';\n > bool = RE_UNC_PATH.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE_UNC_PATH.test( path )\n false\n\n See Also\n --------\n isUNCPath\n","RE_UTF16_SURROGATE_PAIR":"\nRE_UTF16_SURROGATE_PAIR\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var bool = RE_UTF16_SURROGATE_PAIR.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE_UTF16_SURROGATE_PAIR.test( 'abcdef' )\n false\n\n See Also\n --------\n RE_UTF16_UNPAIRED_SURROGATE\n","RE_UTF16_UNPAIRED_SURROGATE":"\nRE_UTF16_UNPAIRED_SURROGATE\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var bool = RE_UTF16_UNPAIRED_SURROGATE.test( 'abc' )\n false\n > bool = RE_UTF16_UNPAIRED_SURROGATE.test( '\\uD800' )\n true\n\n See Also\n --------\n RE_UTF16_SURROGATE_PAIR\n","RE_WHITESPACE":"\nRE_WHITESPACE\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var bool = RE_WHITESPACE.test( '\\n' )\n true\n > bool = RE_WHITESPACE.test( ' ' )\n true\n > bool = RE_WHITESPACE.test( 'a' )\n false\n\n See Also\n --------\n isWhitespace\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n","readFile":"\nreadFile( file[, options,] clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, readDir, readJSON, writeFile\n","readFileList":"\nreadFileList( filepaths[, options,] clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path\n - data: file contents as either a Buffer or string\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readJSON":"\nreadJSON( file[, options,] clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n","readWASM":"\nreadWASM( file, [options,] clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n","real":"\nreal( z )\n Returns the real component of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n","reduce":"\nreduce( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) { return acc + v; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduce( arr, 0, sum )\n 6.0\n\n See Also\n --------\n forEach, reduceAsync, reduceRight\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n","reduceRight":"\nreduceRight( collection, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, the reduction function is provided four arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n If provided an empty collection, the function returns the initial value.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function sum( acc, v ) {\n ... console.log( '%s: %d', acc, v );\n ... return acc + v;\n ... };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = reduceRight( arr, 0, sum );\n 2: 3.0\n 1: 2.0\n 0: 1.0\n > out\n 6.0\n\n See Also\n --------\n forEachRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - `accumulator`: accumulated value\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `next`\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - `accumulator`\n - `value`\n - `index`\n - `next`\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - `error`: error argument\n - `accumulator`: accumulated value\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reim":"\nreim( z )\n Returns the real and imaginary components of a complex number.\n\n Parameters\n ----------\n z: Complex\n Complex number.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n","removeFirst":"\nremoveFirst( str )\n Removes the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n\n See Also\n --------\n removeLast\n","removeLast":"\nremoveLast( str )\n Removes the last character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n\n See Also\n --------\n removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n reverseArguments\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n","replace":"\nreplace( str, search, newval )\n Replaces `search` occurrences with a replacement `string`.\n\n When provided a `string` as the `search` value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","resolveParentPath":"\nresolveParentPath( path[, options,] clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n reorderArguments\n","reverseString":"\nreverseString( str )\n Reverses a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer)\n - data: buffer data as an array of integers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\")\n - re: real component (number)\n - im: imaginary component (number)\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\")\n - data: typed array data as an array of numbers\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n ltrim, trim\n","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 })\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 })\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 })\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false })\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs })\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false })\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 });\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 });\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 });\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' });\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' });\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n - complex128: 128-bit complex numbers\n - complex64: 64-bit complex numbers\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - `value`\n - `next`\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `result`: test result\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year\n - name: President name\n - party: the President's political party\n - text: speech text\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group)\n - group: message group\n - checksum: object containing checksum info\n - text: message text (including headers)\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages)\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages)\n - hard-ham-1: harder to detect non-spam e-mails (250 messages)\n - spam-1: spam e-mails (500 messages)\n - spam-2: spam e-mails collected at a later date (1396 messages)\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5)\n - value: checksum value\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value\n - index: iterated value index\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a `string` starts with the characters of another `string`.\n\n If provided an empty `search` string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a `string` starts with the characters of\n another `string`.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value\n - index: iterated value index\n - n: iteration count (zero-based)\n - src: source array-like object\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n not invoke an array's `@@iterator` method, regardless of whether this method\n is defined. To convert an array to an implementation defined iterator,\n invoke this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'wrap', the function wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - `value`: collection value\n - `index`: collection index\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value\n - 1: value count\n - 2: frequency percentage\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n - `next`: a callback to be invoked after processing a collection `value`\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - `value`\n - `next`\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - `value`\n - `index`\n - `next`\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - `error`: error argument\n - `group`: value group\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` options is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts two arguments:\n\n - error: error object\n - result: function result\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object\n - result: either the result of `x` or the provided argument `y`\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`\n - clbk: callback to invoke upon function completion\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 });\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' });\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' });\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' })\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type\n - data: typed array data as a generic array\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n","typedarrayComplexCtors":"\ntypedarrayComplexCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayComplexCtors( 'complex64' )\n \n > ctor = typedarrayComplexCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors\n","typedarrayComplexDataTypes":"\ntypedarrayComplexDataTypes()\n Returns a list of complex typed array data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = typedarrayComplexDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, ndarrayDataTypes\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n The output array contains the following data types:\n\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr )\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear()\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers\n - float32: single-precision floating-point numbers\n - float16: half-precision floating-point numbers\n - int32: 32-bit two's complement signed integers\n - uint32: 32-bit unsigned integers\n - int16: 16-bit two's complement signed integers\n - uint16: 16-bit unsigned integers\n - int8: 8-bit two's complement signed integers\n - uint8: 8-bit unsigned integers\n - uint8c: 8-bit unsigned integers clamped to 0-255\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...[, elementN]]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element: number\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn );\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n [ 1, 2, 3 ]\n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 1\n > arr2[ 1 ]\n 2\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - `+`: enable\n - `-`: disable\n - `=`: enable specified and disable unspecified permissions\n\n For example,\n\n - `u-w`: disable user write permissions\n - `u+w`: enable user write permissions\n - `u=w`: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n","uppercase":"\nuppercase( str )\n Converts a `string` to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `clbk`: a callback indicating whether to invoke `fcn`\n\n The `clbk` function accepts two arguments:\n\n - `error`: error argument\n - `bool`: test result\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - `i`: iteration number (starting from zero)\n - `next`: a callback which must be invoked before proceeding to the next\n iteration\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - `value`: collection value\n - `index`: collection index\n - `collection`: the input collection\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - `i`: iteration number (starting from zero)\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options,] clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 });\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 });\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 })\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' })\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' })\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' });\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 });\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 })\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/help/scripts/build.js b/lib/node_modules/@stdlib/repl/help/scripts/build.js index 5bfe70f87b26..69ba2fc0dd2e 100644 --- a/lib/node_modules/@stdlib/repl/help/scripts/build.js +++ b/lib/node_modules/@stdlib/repl/help/scripts/build.js @@ -33,7 +33,7 @@ var dirname = require( '@stdlib/utils/dirname' ); var replace = require( '@stdlib/string/replace' ); var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var namespace = require( '@stdlib/namespace' ); -var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); +var pkg2alias = require( '@stdlib/namespace/pkg2alias' ); // VARIABLES // @@ -164,7 +164,7 @@ function main() { tmp = unique( tmp ); for ( j = 0; j < tmp.length; j++ ) { p = RE_ALIAS.exec( tmp[ j ] )[ 1 ]; // extracts a package identifier - a = alias2pkg( p ); + a = pkg2alias( p ); if ( a === null ) { debug( 'Unable to resolve alias: %s.', p ); console.warn( 'WARNING: unable to resolve alias `%s` for `%s`. ', p, alias ); // eslint-disable-line no-console @@ -180,7 +180,7 @@ function main() { tmp = []; related = ns[ i ].related; for ( j = 0; j < len; j++ ) { - a = alias2pkg( related[ j ] ); + a = pkg2alias( related[ j ] ); if ( a === null ) { debug( 'Unable to resolve related alias: %s.', related[ j ] ); console.warn( 'WARNING: unable to resolve related alias `%s` for `%s`. ', related[ j ], alias ); // eslint-disable-line no-console From e7f6e8d44f77e9fca4965d5ac0eeddb6ed82d179 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 19:24:19 -0700 Subject: [PATCH 115/142] Refactor database generation and package API --- .../@stdlib/repl/code-blocks/LICENSE | 356 +++ .../@stdlib/repl/code-blocks/README.md | 115 +- .../repl/code-blocks/benchmark/benchmark.js | 23 +- .../@stdlib/repl/code-blocks/bin/cli | 64 + .../@stdlib/repl/code-blocks/data/data.csv | 1885 ++++++++++++++++ .../@stdlib/repl/code-blocks/data/data.json | 1 + .../@stdlib/repl/code-blocks/datapackage.json | 61 + .../@stdlib/repl/code-blocks/docs/repl.txt | 21 + .../repl/code-blocks/docs/types/index.d.ts | 35 + .../repl/code-blocks/docs/types/test.ts | 44 + .../@stdlib/repl/code-blocks/docs/usage.txt | 8 + .../repl/code-blocks/etc/cli_opts.json | 15 + .../repl/code-blocks/examples/index.js | 21 +- .../@stdlib/repl/code-blocks/lib/db.js | 1914 ----------------- .../@stdlib/repl/code-blocks/lib/index.js | 14 +- .../@stdlib/repl/code-blocks/lib/main.js | 29 +- .../@stdlib/repl/code-blocks/package.json | 10 +- .../@stdlib/repl/code-blocks/scripts/build.js | 84 +- .../@stdlib/repl/code-blocks/test/test.cli.js | 184 ++ .../@stdlib/repl/code-blocks/test/test.js | 69 +- 20 files changed, 2936 insertions(+), 2017 deletions(-) create mode 100644 lib/node_modules/@stdlib/repl/code-blocks/LICENSE create mode 100755 lib/node_modules/@stdlib/repl/code-blocks/bin/cli create mode 100644 lib/node_modules/@stdlib/repl/code-blocks/data/data.csv create mode 100644 lib/node_modules/@stdlib/repl/code-blocks/data/data.json create mode 100644 lib/node_modules/@stdlib/repl/code-blocks/datapackage.json create mode 100644 lib/node_modules/@stdlib/repl/code-blocks/docs/repl.txt create mode 100644 lib/node_modules/@stdlib/repl/code-blocks/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/repl/code-blocks/docs/types/test.ts create mode 100644 lib/node_modules/@stdlib/repl/code-blocks/docs/usage.txt create mode 100644 lib/node_modules/@stdlib/repl/code-blocks/etc/cli_opts.json delete mode 100644 lib/node_modules/@stdlib/repl/code-blocks/lib/db.js create mode 100644 lib/node_modules/@stdlib/repl/code-blocks/test/test.cli.js diff --git a/lib/node_modules/@stdlib/repl/code-blocks/LICENSE b/lib/node_modules/@stdlib/repl/code-blocks/LICENSE new file mode 100644 index 000000000000..dc6d53e33997 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/LICENSE @@ -0,0 +1,356 @@ +The use of the database is licensed under an Open Data Commons Public Domain +Dedication & License 1.0 (PDDL 1.0), while the database contents are licensed +under Creative Commons Zero v1.0 Universal (CC0 1.0). The software is licensed +under an Apache-2.0 license. + + + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. 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Some jurisdictions do not allow the exclusion of implied warranties, so this exclusion may not apply to You. + +5.2 Subject to any liability that may not be excluded or limited by law, the Rightsholder is not liable for, and expressly excludes, all liability for loss or damage however and whenever caused to anyone by any use under this Document, whether by You or by anyone else, and whether caused by any fault on the part of the Rightsholder or not. This exclusion of liability includes, but is not limited to, any special, incidental, consequential, punitive, or exemplary damages. This exclusion applies even if the Rightsholder has been advised of the possibility of such damages. + +5.3 If liability may not be excluded by law, it is limited to actual and direct financial loss to the extent it is caused by proved negligence on the part of the Rightsholder. + +6.0 General + +6.1 If any provision of this Document is held to be invalid or unenforceable, that must not affect the validity or enforceability of the remainder of the terms of this Document. + +6.2 This Document is the entire agreement between the parties with respect to the Work covered here. It replaces any earlier understandings, agreements or representations with respect to the Work not specified here. + +6.3 This Document does not affect any rights that You or anyone else may independently have under any applicable law to make any use of this Work, including (for jurisdictions where this Document is a licence) fair dealing, fair use, database exceptions, or any other legally recognised limitation or exception to infringement of copyright or other applicable laws. + +6.4 This Document takes effect in the relevant jurisdiction in which the Document terms are sought to be enforced. If the rights waived or granted under applicable law in the relevant jurisdiction includes additional rights not waived or granted under this Document, these additional rights are included in this Document in order to meet the intent of this Document. diff --git a/lib/node_modules/@stdlib/repl/code-blocks/README.md b/lib/node_modules/@stdlib/repl/code-blocks/README.md index 47e3cd76cfb4..714c2da6d33a 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/README.md +++ b/lib/node_modules/@stdlib/repl/code-blocks/README.md @@ -2,7 +2,7 @@ @license Apache-2.0 -Copyright (c) 2018 The Stdlib Authors. +Copyright (c) 2019 The Stdlib Authors. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -20,7 +20,7 @@ limitations under the License. # Examples -> REPL examples. +> Return an example associated with a provided alias. @@ -37,16 +37,23 @@ limitations under the License. ## Usage ```javascript -var examples = require( '@stdlib/repl/code-blocks' ); +var example = require( '@stdlib/repl/code-blocks' ); ``` -#### examples() +#### example( alias ) -Returns an `object` containing REPL examples as text. +Returns an example associated with a provided alias. ```javascript -var o = examples(); -// returns {...} +var out = example( 'base.sin' ); +// returns +``` + +If provided an unrecognized `alias`, the function returns `null`. + +```javascript +var out = example( 'unrecognized_alias_beep_boop_bop_bip' ); +// returns null ``` @@ -72,17 +79,89 @@ var o = examples(); ```javascript -var examples = require( '@stdlib/repl/code-blocks' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var example = require( '@stdlib/repl/code-blocks' ); + +var list; +var len; +var idx; +var i; + +list = aliases(); +len = list.length; + +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len-1 ); + console.log( example( list[ idx ] ) ); +} +``` + + + + + + + +
+ +
+ + + + + +* * * + +
+ +## CLI + + + +
+ +### Usage + +```text +Usage: stdlib-alias-example [options] + +Options: -var o = examples(); -console.log( o ); -// => {...} + -h, --help Print this message. + -V, --version Print the package version. +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```bash +$ stdlib-alias-example 'base.sin' ```
+
+ + +
@@ -91,10 +170,24 @@ console.log( o ); + + +## License + +The data files (databases) are licensed under an [Open Data Commons Public Domain Dedication & License 1.0][pddl-1.0] and their contents are licensed under [Creative Commons Zero v1.0 Universal][cc0]. The software is licensed under [Apache License, Version 2.0][apache-license]. + + +
+[pddl-1.0]: http://opendatacommons.org/licenses/pddl/1.0/ + +[cc0]: https://creativecommons.org/publicdomain/zero/1.0 + +[apache-license]: https://www.apache.org/licenses/LICENSE-2.0 +
diff --git a/lib/node_modules/@stdlib/repl/code-blocks/benchmark/benchmark.js b/lib/node_modules/@stdlib/repl/code-blocks/benchmark/benchmark.js index a18b163b3e43..5281feb9c100 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/benchmark/benchmark.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -21,26 +21,31 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var isPlainObject = require( '@stdlib/assert/is-plain-object' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var aliases = require( '@stdlib/namespace/aliases' ); var pkg = require( './../package.json' ).name; -var examples = require( './../lib' ); +var example = require( './../lib' ); // MAIN // bench( pkg, function benchmark( b ) { - var o; + var values; + var v; var i; + + values = aliases(); + b.tic(); for ( i = 0; i < b.iterations; i++ ) { - o = examples(); - if ( typeof o !== 'object' ) { - b.fail( 'should return an object' ); + v = example( values[ i%values.length ] ); + if ( typeof v !== 'string' ) { + b.fail( 'should return a string' ); } } b.toc(); - if ( !isPlainObject( o ) ) { - b.fail( 'should return a plain object' ); + if ( !isString( v ) ) { + b.fail( 'should return a string' ); } b.pass( 'benchmark finished' ); b.end(); diff --git a/lib/node_modules/@stdlib/repl/code-blocks/bin/cli b/lib/node_modules/@stdlib/repl/code-blocks/bin/cli new file mode 100755 index 000000000000..ca5a235b2280 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/bin/cli @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var readFileSync = require( '@stdlib/fs/read-file' ).sync; +var CLI = require( '@stdlib/tools/cli' ); +var example = require( './../lib' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var args; + var cli; + var out; + + // Create a command-line interface: + cli = new CLI({ + 'pkg': require( './../package.json' ), + 'options': require( './../etc/cli_opts.json' ), + 'help': readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }) + }); + + // Get any provided command-line arguments: + args = cli.args(); + + // Print an example corresponding to a provided alias... + out = example( args[ 0 ] ); + if ( out ) { + console.log( out ); // eslint-disable-line no-console + } else { + cli.exit( 1 ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv new file mode 100644 index 000000000000..b2bb18f6ba79 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv @@ -0,0 +1,1885 @@ +AFINN_96,"var list = AFINN_96()\n" +AFINN_111,"var list = AFINN_111()\n" +alias2pkg,"var v = alias2pkg( 'base.sin' )\n" +alias2related,"var v = alias2related( 'base.sin' )\n" +aliases,"var o = aliases()\n" +allocUnsafe,"var buf = allocUnsafe( 100 )\n" +anova1,"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n'control', 'treatA', 'treatB', 'treatC', 'control',\n'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n];\nvar out = anova1( x, f )\n" +ANSCOMBES_QUARTET,"var d = ANSCOMBES_QUARTET()\n" +any,"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n" +anyBy,"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n" +anyByAsync,"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n" +anyByRight,"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n" +anyByRightAsync,"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n" +APERY,"APERY\n" +append,"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\n\n// Array-like object:\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n" +ARCH,"ARCH\n" +argumentFunction,"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n" +ARGV,"var execPath = ARGV[ 0 ]\n" +array,"\n// Create a 2x2 matrix:\nvar arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n\n// Get an element using subscripts:\nvar v = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n" +array2buffer,"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n" +array2iterator,"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n" +array2iteratorRight,"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n" +ArrayBuffer,"var buf = new ArrayBuffer( 5 )\n" +arraybuffer2buffer,"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n" +arrayCtors,"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n" +arrayDataType,"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n" +arrayDataTypes,"var out = arrayDataTypes()\n" +arrayMinDataType,"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n" +arrayNextDataType,"var out = arrayNextDataType( 'float32' )\n" +arrayPromotionRules,"var out = arrayPromotionRules( 'float32', 'int32' )\n" +arraySafeCasts,"var out = arraySafeCasts( 'float32' )\n" +arraySameKindCasts,"var out = arraySameKindCasts( 'float32' )\n" +arrayShape,"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n" +arrayStream,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +arrayview2iterator,"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n" +arrayview2iteratorRight,"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n" +AsyncIteratorSymbol,"var s = AsyncIteratorSymbol\n" +bartlettTest,"\n// Data from Hollander & Wolfe (1973), p. 116:\nvar x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n];\nout = bartlettTest( arr, { 'groups': groups })\n" +base.abs,"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n" +base.abs2,"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n" +base.absdiff,"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n" +base.absInt32,"var v = base.absInt32( -1|0 )\nv = base.absInt32( 2|0 )\nv = base.absInt32( 0|0 )\n" +base.acos,"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n" +base.acosh,"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n" +base.acoth,"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n" +base.acovercos,"var y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n" +base.acoversin,"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n" +base.ahavercos,"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n" +base.ahaversin,"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n" +base.asin,"var y = base.asin( 0.0 )\ny = base.asin( PI/2.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n" +base.asinh,"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n" +base.atan,"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n" +base.atan2,"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n" +base.atanh,"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n" +base.avercos,"var y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n" +base.aversin,"var y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n" +base.bernoulli,"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n" +base.besselj0,"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n" +base.besselj1,"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n" +base.bessely0,"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n" +base.bessely1,"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n" +base.beta,"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n" +base.betainc,"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n" +base.betaincinv,"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n" +base.betaln,"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n" +base.binet,"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n" +base.binomcoef,"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n" +base.binomcoefln,"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n" +base.boxcox,"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n" +base.boxcox1p,"var v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n" +base.boxcox1pinv,"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n" +base.boxcoxinv,"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n" +base.cabs,"var y = base.cabs( 5.0, 3.0 )\n" +base.cabs2,"var y = base.cabs2( 5.0, 3.0 )\n" +base.cadd,"var y = base.cadd( 5.0, 3.0, -2.0, 1.0 )\n\n// Provide an output array:\nvar out = new Float32Array( 2 );\ny = base.cadd( out, 5.0, 3.0, -2.0, 1.0 )\nvar bool = ( y === out )\n" +base.cbrt,"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n" +base.cceil,"var out = base.cceil( 5.5, 3.3 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cceil( out, 5.5, 3.3 )\nvar bool = ( v === out )\n" +base.cceiln,"var out = base.cceiln( 5.555, -3.333, -2 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cceiln( out, 5.555, -3.333, -2 )\nvar bool = ( v === out )\n" +base.ccis,"var y = base.ccis( 0.0, 0.0 )\nvar y = base.ccis( 1.0, 0.0 )\nvar out = new Float64Array( 2 );\nvar v = base.ccis( out, 1.0, 0.0 )\nvar bool = ( v === out )\n" +base.cdiv,"var y = base.cdiv( -13.0, -1.0, -2.0, 1.0 )\nvar out = new Float64Array( 2 );\nvar v = base.cdiv( out, -13.0, -1.0, -2.0, 1.0 )\nvar bool = ( v === out )\n" +base.ceil,"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n" +base.ceil2,"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n" +base.ceil10,"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n" +base.ceilb,"\n// Round to 4 decimal places:\nvar y = base.ceilb( 3.14159, -4, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.ceilb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two toward positive infinity:\ny = base.ceilb( 5.0, 1, 2 )\n" +base.ceiln,"\n// Round to 2 decimal places:\nvar y = base.ceiln( 3.14159, -2 )\n\n// If `n = 0`, standard round toward positive infinity behavior:\ny = base.ceiln( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.ceiln( 12368.0, 3 )\n" +base.ceilsd,"var y = base.ceilsd( 3.14159, 5 )\ny = base.ceilsd( 3.14159, 1 )\ny = base.ceilsd( 12368.0, 2 )\ny = base.ceilsd( 0.0313, 2, 2 )\n" +base.cexp,"var y = base.cexp( 0.0, 0.0 )\ny = base.cexp( 0.0, 1.0 )\nvar out = new Float64Array( 2 );\nvar v = base.cexp( out, 0.0, 1.0 )\nvar bool = ( v === out )\n" +base.cflipsign,"var out = base.cflipsign( -4.2, 5.5, -9 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cflipsign( out, -4.2, 5.5, 8 )\nvar bool = ( v === out )\n" +base.cfloor,"var out = base.cfloor( 5.5, 3.3 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cfloor( out, 5.5, 3.3 )\nvar bool = ( v === out )\n" +base.cfloorn,"var out = base.cfloorn( 5.555, -3.333, -2 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cfloorn( out, 5.555, -3.333, -2 )\nvar bool = ( v === out )\n" +base.cinv,"var y = base.cinv( 2.0, 4.0 )\nvar out = new Float64Array( 2 );\nvar v = base.cinv( out, 2.0, 4.0 )\nvar bool = ( v === out )\n" +base.clamp,"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n" +base.cmul,"var out = base.cmul( 5.0, 3.0, -2.0, 1.0 )\n\n// Provide an output array:\nvar out = new Float64Array( 2 );\nvar v = base.cmul( out, 5.0, 3.0, -2.0, 1.0 )\nvar bool = ( v === out )\n" +base.cneg,"var out = base.cneg( -4.2, 5.5 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cneg( out, -4.2, 5.5 )\nvar bool = ( v === out )\n" +base.continuedFraction,"\n// Continued fraction for (e-1)^(-1):\nfunction closure() {\n var i = 0;\n return function() {\n i += 1;\n return [ i, i ];\n };\n};\nvar gen = closure();\nvar out = base.continuedFraction( gen )\n\n// Using an ES6 generator:\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n};\ngen = generator();\nout = base.continuedFraction( gen )\n\n// Set options:\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n" +base.copysign,"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n" +base.cos,"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n" +base.cosh,"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n" +base.cosm1,"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n" +base.cospi,"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n" +base.covercos,"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n" +base.coversin,"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n" +base.cphase,"var phi = base.cphase( 5.0, 3.0 )\n" +base.cpolar,"var out = base.cpolar( 5.0, 3.0 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cpolar( out, 5.0, 3.0 )\nvar bool = ( v === out )\n" +base.cround,"var out = base.cround( 5.5, 3.3 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cround( out, 5.5, 3.3 )\nvar bool = ( v === out )\n" +base.croundn,"var out = base.croundn( 5.555, -3.336, -2 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.croundn( out, 5.555, -3.336, -2 )\nvar bool = ( v === out )\n" +base.csignum,"var out = base.csignum( -4.2, 5.5 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.csignum( out, -4.2, 5.5 )\nvar bool = ( v === out )\n" +base.csub,"var out = base.csub( 5.0, 3.0, -2.0, 1.0 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.csub( out, 5.0, 3.0, -2.0, 1.0 )\nvar bool = ( v === out )\n" +base.dasum,"\n// Standard usage:\nvar x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\nvar sum = base.dasum( x.length, x, 1 )\n\n// Sum every other value:\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nsum = base.dasum( N, x, stride )\n\n// Use view offset; e.g., starting at 2nd element:\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nsum = base.dasum( N, x1, stride )\n" +base.daxpy,"\n// Standard usage:\nvar x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.daxpy( x.length, alpha, x, 1, y, 1 )\n\n// Using `N` and `stride` parameters:\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.daxpy( N, alpha, x, 2, y, -1 )\n\n// Using view offsets:\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.daxpy( N, 5.0, x1, -2, y1, 1 )\ny0\n" +base.dcopy,"\n// Standard usage:\nvar x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.dcopy( x.length, x, 1, y, 1 )\n\n// Advanced indexing:\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.dcopy( N, x, -2, y, 1 )\n\n// Using typed array views:\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.dcopy( N, x1, -2, y1, 1 )\ny0\n" +base.deg2rad,"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n" +base.digamma,"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n" +base.diracDelta,"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n" +base.dists.arcsine.Arcsine,"var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n" +base.dists.arcsine.cdf,"var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n" +base.dists.arcsine.entropy,"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n" +base.dists.arcsine.kurtosis,"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n" +base.dists.arcsine.logcdf,"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n" +base.dists.arcsine.logpdf,"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n" +base.dists.arcsine.mean,"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n" +base.dists.arcsine.median,"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n" +base.dists.arcsine.mode,"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n" +base.dists.arcsine.pdf,"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n" +base.dists.arcsine.quantile,"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n" +base.dists.arcsine.skewness,"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n" +base.dists.arcsine.stdev,"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n" +base.dists.arcsine.variance,"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n" +base.dists.bernoulli.Bernoulli,"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n" +base.dists.bernoulli.cdf,"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\n\n// Invalid probability:\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n" +base.dists.bernoulli.entropy,"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n" +base.dists.bernoulli.kurtosis,"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n" +base.dists.bernoulli.mean,"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n" +base.dists.bernoulli.median,"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n" +base.dists.bernoulli.mgf,"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n" +base.dists.bernoulli.mode,"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n" +base.dists.bernoulli.pmf,"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\n\n// Invalid success probability:\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n" +base.dists.bernoulli.quantile,"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n" +base.dists.bernoulli.skewness,"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n" +base.dists.bernoulli.stdev,"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n" +base.dists.bernoulli.variance,"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n" +base.dists.beta.Beta,"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n" +base.dists.beta.cdf,"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n" +base.dists.beta.entropy,"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n" +base.dists.beta.kurtosis,"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n" +base.dists.beta.logcdf,"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n" +base.dists.beta.logpdf,"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n" +base.dists.beta.mean,"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n" +base.dists.beta.median,"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n" +base.dists.beta.mgf,"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n" +base.dists.beta.mode,"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n" +base.dists.beta.pdf,"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n" +base.dists.beta.quantile,"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n" +base.dists.beta.skewness,"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n" +base.dists.beta.stdev,"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n" +base.dists.beta.variance,"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n" +base.dists.betaprime.BetaPrime,"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n" +base.dists.betaprime.cdf,"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n" +base.dists.betaprime.kurtosis,"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n" +base.dists.betaprime.logcdf,"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n" +base.dists.betaprime.logpdf,"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n" +base.dists.betaprime.mean,"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n" +base.dists.betaprime.mode,"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n" +base.dists.betaprime.pdf,"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n" +base.dists.betaprime.quantile,"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n" +base.dists.betaprime.skewness,"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n" +base.dists.betaprime.stdev,"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n" +base.dists.betaprime.variance,"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n" +base.dists.binomial.Binomial,"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n" +base.dists.binomial.cdf,"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n" +base.dists.binomial.entropy,"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n" +base.dists.binomial.kurtosis,"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n" +base.dists.binomial.logpmf,"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n" +base.dists.binomial.mean,"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n" +base.dists.binomial.median,"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n" +base.dists.binomial.mgf,"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n" +base.dists.binomial.mode,"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n" +base.dists.binomial.pmf,"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n" +base.dists.binomial.quantile,"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n" +base.dists.binomial.skewness,"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n" +base.dists.binomial.stdev,"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n" +base.dists.binomial.variance,"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n" +base.dists.cauchy.Cauchy,"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n" +base.dists.cauchy.cdf,"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n" +base.dists.cauchy.entropy,"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n" +base.dists.cauchy.logcdf,"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n" +base.dists.cauchy.logpdf,"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n" +base.dists.cauchy.median,"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n" +base.dists.cauchy.mode,"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n" +base.dists.cauchy.pdf,"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n" +base.dists.cauchy.quantile,"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n" +base.dists.chi.cdf,"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chi.cdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n" +base.dists.chi.Chi,"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n" +base.dists.chi.entropy,"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n" +base.dists.chi.kurtosis,"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n" +base.dists.chi.logpdf,"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chi.logpdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n" +base.dists.chi.mean,"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n" +base.dists.chi.mode,"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n" +base.dists.chi.pdf,"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chi.pdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n" +base.dists.chi.quantile,"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chi.quantile( 0.5, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n" +base.dists.chi.skewness,"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n" +base.dists.chi.stdev,"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n" +base.dists.chi.variance,"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n" +base.dists.chisquare.cdf,"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n" +base.dists.chisquare.ChiSquare,"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n" +base.dists.chisquare.entropy,"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n" +base.dists.chisquare.kurtosis,"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n" +base.dists.chisquare.logpdf,"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n" +base.dists.chisquare.mean,"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n" +base.dists.chisquare.mode,"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n" +base.dists.chisquare.pdf,"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n" +base.dists.chisquare.quantile,"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n" +base.dists.chisquare.skewness,"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n" +base.dists.chisquare.stdev,"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n" +base.dists.chisquare.variance,"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n" +base.dists.cosine.cdf,"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n\n// Degenerate distribution centered at `μ` when `s = 0.0`:\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n" +base.dists.cosine.Cosine,"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n" +base.dists.cosine.kurtosis,"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n" +base.dists.cosine.logcdf,"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n\n// Degenerate distribution centered at `μ` when `s = 0.0`:\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n" +base.dists.cosine.logpdf,"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution at `s = 0.0`:\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n" +base.dists.cosine.mean,"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n" +base.dists.cosine.median,"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n" +base.dists.cosine.mgf,"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n" +base.dists.cosine.mode,"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n" +base.dists.cosine.pdf,"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n" +base.dists.cosine.quantile,"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n" +base.dists.cosine.skewness,"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n" +base.dists.cosine.stdev,"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n" +base.dists.cosine.variance,"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n" +base.dists.degenerate.cdf,"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n" +base.dists.degenerate.Degenerate,"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n" +base.dists.degenerate.entropy,"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n" +base.dists.degenerate.logcdf,"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n" +base.dists.degenerate.logpdf,"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n" +base.dists.degenerate.logpmf,"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n" +base.dists.degenerate.mean,"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n" +base.dists.degenerate.median,"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n" +base.dists.degenerate.mgf,"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n" +base.dists.degenerate.mode,"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n" +base.dists.degenerate.pdf,"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n" +base.dists.degenerate.pmf,"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n" +base.dists.degenerate.quantile,"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n" +base.dists.degenerate.stdev,"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n" +base.dists.degenerate.variance,"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n" +base.dists.discreteUniform.cdf,"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n" +base.dists.discreteUniform.DiscreteUniform,"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n" +base.dists.discreteUniform.kurtosis,"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n" +base.dists.discreteUniform.logcdf,"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n" +base.dists.discreteUniform.logpmf,"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n" +base.dists.discreteUniform.mean,"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n" +base.dists.discreteUniform.median,"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n" +base.dists.discreteUniform.mgf,"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n" +base.dists.discreteUniform.pmf,"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n" +base.dists.discreteUniform.quantile,"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n" +base.dists.discreteUniform.skewness,"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n" +base.dists.discreteUniform.stdev,"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n" +base.dists.discreteUniform.variance,"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n" +base.dists.erlang.cdf,"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n" +base.dists.erlang.entropy,"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n" +base.dists.erlang.Erlang,"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n" +base.dists.erlang.kurtosis,"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n" +base.dists.erlang.logpdf,"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n" +base.dists.erlang.mean,"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n" +base.dists.erlang.mgf,"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n" +base.dists.erlang.mode,"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n" +base.dists.erlang.pdf,"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n" +base.dists.erlang.quantile,"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\n\n// Non-integer shape parameter:\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n\n// Non-positive shape parameter:\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n" +base.dists.erlang.skewness,"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n" +base.dists.erlang.stdev,"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n" +base.dists.erlang.variance,"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n" +base.dists.exponential.cdf,"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\n\n// Negative rate parameter:\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n" +base.dists.exponential.entropy,"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n" +base.dists.exponential.Exponential,"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n" +base.dists.exponential.kurtosis,"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n" +base.dists.exponential.logcdf,"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\n\n// Negative rate parameter:\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n" +base.dists.exponential.logpdf,"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\n\n// Negative rate:\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n" +base.dists.exponential.mean,"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n" +base.dists.exponential.median,"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n" +base.dists.exponential.mode,"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n" +base.dists.exponential.pdf,"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\n\n// Negative rate:\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n" +base.dists.exponential.quantile,"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\n\n// Negative rate parameter:\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n" +base.dists.exponential.skewness,"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n" +base.dists.exponential.stdev,"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n" +base.dists.exponential.variance,"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n" +base.dists.f.cdf,"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\nvar y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n" +base.dists.f.entropy,"var v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n" +base.dists.f.F,"var f = base.dists.f.F( 6.0, 9.0 );\nf.d1\nf.d2\nf.entropy\nf.kurtosis\nf.mean\nf.mode\nf.skewness\nf.stdev\nf.variance\nf.cdf( 3.0 )\nf.pdf( 2.5 )\nf.quantile( 0.8 )\n" +base.dists.f.kurtosis,"var v = base.dists.f.kurtosis( 3.0, 9.0 )\nv = base.dists.f.kurtosis( 4.0, 12.0 )\nv = base.dists.f.kurtosis( 8.0, 9.0 )\n" +base.dists.f.mean,"var v = base.dists.f.mean( 3.0, 5.0 )\nv = base.dists.f.mean( 4.0, 12.0 )\nv = base.dists.f.mean( 8.0, 4.0 )\n" +base.dists.f.mode,"var v = base.dists.f.mode( 3.0, 5.0 )\nv = base.dists.f.mode( 4.0, 12.0 )\nv = base.dists.f.mode( 8.0, 4.0 )\n" +base.dists.f.pdf,"var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n" +base.dists.f.quantile,"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n" +base.dists.f.skewness,"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n" +base.dists.f.stdev,"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n" +base.dists.f.variance,"var v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = base.dists.f.variance( 8.0, 5.0 )\n" +base.dists.frechet.cdf,"var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n" +base.dists.frechet.entropy,"var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\ny = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\ny = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\ny = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n" +base.dists.frechet.Frechet,"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n" +base.dists.frechet.kurtosis,"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n" +base.dists.frechet.logcdf,"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n" +base.dists.frechet.logpdf,"var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n" +base.dists.frechet.mean,"var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n" +base.dists.frechet.median,"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n" +base.dists.frechet.mode,"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n" +base.dists.frechet.pdf,"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n" +base.dists.frechet.quantile,"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n" +base.dists.frechet.skewness,"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n" +base.dists.frechet.stdev,"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n" +base.dists.frechet.variance,"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n" +base.dists.gamma.cdf,"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0` when `α = 0.0`:\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n" +base.dists.gamma.entropy,"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n" +base.dists.gamma.Gamma,"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n" +base.dists.gamma.kurtosis,"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n" +base.dists.gamma.logpdf,"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0.0` when `α = 0.0`:\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n" +base.dists.gamma.mean,"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n" +base.dists.gamma.mgf,"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n" +base.dists.gamma.mode,"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n" +base.dists.gamma.pdf,"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0.0` when `α = 0.0`:\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n" +base.dists.gamma.quantile,"var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n\n// Non-positive shape parameter:\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0.0` when `α = 0.0`:\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n" +base.dists.gamma.skewness,"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n" +base.dists.gamma.stdev,"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n" +base.dists.gamma.variance,"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n" +base.dists.geometric.cdf,"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\n\n// Invalid probability\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n" +base.dists.geometric.entropy,"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n" +base.dists.geometric.Geometric,"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n" +base.dists.geometric.kurtosis,"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n" +base.dists.geometric.logcdf,"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\n\n// Invalid probability\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n" +base.dists.geometric.logpmf,"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\n\n// Invalid success probability:\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n" +base.dists.geometric.mean,"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n" +base.dists.geometric.median,"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n" +base.dists.geometric.mgf,"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\n\n// Case: t >= -ln(1-p)\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n" +base.dists.geometric.mode,"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n" +base.dists.geometric.pmf,"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\n\n// Invalid success probability:\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n" +base.dists.geometric.quantile,"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n" +base.dists.geometric.skewness,"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n" +base.dists.geometric.stdev,"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n" +base.dists.geometric.variance,"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n" +base.dists.gumbel.cdf,"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n" +base.dists.gumbel.entropy,"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n" +base.dists.gumbel.Gumbel,"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n" +base.dists.gumbel.kurtosis,"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n" +base.dists.gumbel.logcdf,"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n" +base.dists.gumbel.logpdf,"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n" +base.dists.gumbel.mean,"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n" +base.dists.gumbel.median,"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n" +base.dists.gumbel.mgf,"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n\n// Case: `t >= 1/beta`\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n\n// Non-positive scale parameter:\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n" +base.dists.gumbel.mode,"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n" +base.dists.gumbel.pdf,"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n" +base.dists.gumbel.quantile,"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n" +base.dists.gumbel.skewness,"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n" +base.dists.gumbel.stdev,"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n" +base.dists.gumbel.variance,"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n" +base.dists.hypergeometric.cdf,"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n" +base.dists.hypergeometric.Hypergeometric,"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n" +base.dists.hypergeometric.kurtosis,"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n" +base.dists.hypergeometric.logpmf,"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n" +base.dists.hypergeometric.mean,"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n" +base.dists.hypergeometric.mode,"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n" +base.dists.hypergeometric.pmf,"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n" +base.dists.hypergeometric.quantile,"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n" +base.dists.hypergeometric.skewness,"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n" +base.dists.hypergeometric.stdev,"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n" +base.dists.hypergeometric.variance,"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n" +base.dists.invgamma.cdf,"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n" +base.dists.invgamma.entropy,"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n" +base.dists.invgamma.InvGamma,"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n" +base.dists.invgamma.kurtosis,"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n" +base.dists.invgamma.logpdf,"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n\n// Negative scale parameter:\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n" +base.dists.invgamma.mean,"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n" +base.dists.invgamma.mode,"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n" +base.dists.invgamma.pdf,"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n\n// Negative scale parameter:\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n" +base.dists.invgamma.quantile,"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n\n// Non-positive shape parameter:\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n" +base.dists.invgamma.skewness,"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n" +base.dists.invgamma.stdev,"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n" +base.dists.invgamma.variance,"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n" +base.dists.kumaraswamy.cdf,"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n" +base.dists.kumaraswamy.Kumaraswamy,"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n" +base.dists.kumaraswamy.kurtosis,"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n" +base.dists.kumaraswamy.logcdf,"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n" +base.dists.kumaraswamy.logpdf,"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n" +base.dists.kumaraswamy.mean,"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n" +base.dists.kumaraswamy.median,"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n" +base.dists.kumaraswamy.mode,"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n" +base.dists.kumaraswamy.pdf,"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n" +base.dists.kumaraswamy.quantile,"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n" +base.dists.kumaraswamy.skewness,"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n" +base.dists.kumaraswamy.stdev,"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n" +base.dists.kumaraswamy.variance,"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n" +base.dists.laplace.cdf,"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n" +base.dists.laplace.entropy,"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n" +base.dists.laplace.kurtosis,"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n" +base.dists.laplace.Laplace,"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n" +base.dists.laplace.logcdf,"var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n" +base.dists.laplace.logpdf,"var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n" +base.dists.laplace.mean,"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n" +base.dists.laplace.median,"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n" +base.dists.laplace.mgf,"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n" +base.dists.laplace.mode,"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n" +base.dists.laplace.pdf,"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n" +base.dists.laplace.quantile,"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n" +base.dists.laplace.skewness,"var y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n" +base.dists.laplace.stdev,"var y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n" +base.dists.laplace.variance,"var y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 )\n" +base.dists.levy.cdf,"var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.cdf( 2, NaN, 1.0 )\ny = base.dists.levy.cdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n" +base.dists.levy.entropy,"var y = base.dists.levy.entropy( 0.0, 1.0 )\ny = base.dists.levy.entropy( 4.0, 2.0 )\ny = base.dists.levy.entropy( NaN, 1.0 )\ny = base.dists.levy.entropy( 0.0, NaN )\ny = base.dists.levy.entropy( 0.0, 0.0 )\n" +base.dists.levy.Levy,"var levy = base.dists.levy.Levy( -2.0, 3.0 );\nlevy.mu\nlevy.c\nlevy.entropy\nlevy.mean\nlevy.median\nlevy.mode\nlevy.stdev\nlevy.variance\nlevy.cdf( 0.8 )\nlevy.logcdf( 0.8 )\nlevy.logpdf( 1.0 )\nlevy.pdf( 1.0 )\nlevy.quantile( 0.8 )\n" +base.dists.levy.logcdf,"var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 2, NaN, 1.0 )\ny = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n" +base.dists.levy.logpdf,"var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n" +base.dists.levy.mean,"var y = base.dists.levy.mean( 0.0, 1.0 )\ny = base.dists.levy.mean( 4.0, 3.0 )\ny = base.dists.levy.mean( NaN, 1.0 )\ny = base.dists.levy.mean( 0.0, NaN )\ny = base.dists.levy.mean( 0.0, 0.0 )\n" +base.dists.levy.median,"var y = base.dists.levy.median( 0.0, 1.0 )\ny = base.dists.levy.median( 4.0, 3.0 )\ny = base.dists.levy.median( NaN, 1.0 )\ny = base.dists.levy.median( 0.0, NaN )\ny = base.dists.levy.median( 0.0, 0.0 )\n" +base.dists.levy.mode,"var y = base.dists.levy.mode( 0.0, 1.0 )\ny = base.dists.levy.mode( 4.0, 3.0 )\ny = base.dists.levy.mode( NaN, 1.0 )\ny = base.dists.levy.mode( 0.0, NaN )\ny = base.dists.levy.mode( 0.0, 0.0 )\n" +base.dists.levy.pdf,"var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.pdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n" +base.dists.levy.quantile,"var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.levy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.levy.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n" +base.dists.levy.stdev,"var y = base.dists.levy.stdev( 0.0, 1.0 )\ny = base.dists.levy.stdev( 4.0, 3.0 )\ny = base.dists.levy.stdev( NaN, 1.0 )\ny = base.dists.levy.stdev( 0.0, NaN )\ny = base.dists.levy.stdev( 0.0, 0.0 )\n" +base.dists.levy.variance,"var y = base.dists.levy.variance( 0.0, 1.0 )\ny = base.dists.levy.variance( 4.0, 3.0 )\ny = base.dists.levy.variance( NaN, 1.0 )\ny = base.dists.levy.variance( 0.0, NaN )\ny = base.dists.levy.variance( 0.0, 0.0 )\n" +base.dists.logistic.cdf,"var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.cdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\ny = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n\n// Degenerate distribution centered at `μ` when `s = 0.0`:\ny = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n" +base.dists.logistic.entropy,"var y = base.dists.logistic.entropy( 0.0, 1.0 )\ny = base.dists.logistic.entropy( 4.0, 2.0 )\ny = base.dists.logistic.entropy( NaN, 1.0 )\ny = base.dists.logistic.entropy( 0.0, NaN )\ny = base.dists.logistic.entropy( 0.0, 0.0 )\n" +base.dists.logistic.kurtosis,"var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\ny = base.dists.logistic.kurtosis( 4.0, 2.0 )\ny = base.dists.logistic.kurtosis( NaN, 1.0 )\ny = base.dists.logistic.kurtosis( 0.0, NaN )\ny = base.dists.logistic.kurtosis( 0.0, 0.0 )\n" +base.dists.logistic.logcdf,"var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.logcdf( 2, NaN, 1.0 )\ny = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n" +base.dists.logistic.Logistic,"var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\nlogistic.mu\nlogistic.s\nlogistic.entropy\nlogistic.kurtosis\nlogistic.mean\nlogistic.median\nlogistic.mode\nlogistic.skewness\nlogistic.stdev\nlogistic.variance\nlogistic.cdf( 0.8 )\nlogistic.logcdf( 0.8 )\nlogistic.logpdf( 2.0 )\nlogistic.mgf( 0.2 )\nlogistic.pdf( 2.0 )\nlogistic.quantile( 0.9 )\n" +base.dists.logistic.logpdf,"var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution at `s = 0.0`:\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n" +base.dists.logistic.mean,"var y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n" +base.dists.logistic.median,"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n" +base.dists.logistic.mgf,"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n" +base.dists.logistic.mode,"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n" +base.dists.logistic.pdf,"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n" +base.dists.logistic.quantile,"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n" +base.dists.logistic.skewness,"var y = base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n" +base.dists.logistic.stdev,"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n" +base.dists.logistic.variance,"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n" +base.dists.lognormal.cdf,"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n" +base.dists.lognormal.entropy,"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n" +base.dists.lognormal.kurtosis,"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n" +base.dists.lognormal.LogNormal,"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n" +base.dists.lognormal.logpdf,"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n" +base.dists.lognormal.mean,"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n" +base.dists.lognormal.median,"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n" +base.dists.lognormal.mode,"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n" +base.dists.lognormal.pdf,"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n" +base.dists.lognormal.quantile,"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n" +base.dists.lognormal.skewness,"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n" +base.dists.lognormal.stdev,"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n" +base.dists.lognormal.variance,"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n" +base.dists.negativeBinomial.cdf,"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n" +base.dists.negativeBinomial.kurtosis,"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n" +base.dists.negativeBinomial.logpmf,"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n" +base.dists.negativeBinomial.mean,"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n" +base.dists.negativeBinomial.mgf,"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n" +base.dists.negativeBinomial.mode,"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n" +base.dists.negativeBinomial.NegativeBinomial,"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n" +base.dists.negativeBinomial.pmf,"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n" +base.dists.negativeBinomial.quantile,"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n" +base.dists.negativeBinomial.skewness,"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n" +base.dists.negativeBinomial.stdev,"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n" +base.dists.negativeBinomial.variance,"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n" +base.dists.normal.cdf,"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n" +base.dists.normal.entropy,"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n" +base.dists.normal.kurtosis,"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n" +base.dists.normal.logpdf,"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n" +base.dists.normal.mean,"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n" +base.dists.normal.median,"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n" +base.dists.normal.mgf,"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n" +base.dists.normal.mode,"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n" +base.dists.normal.Normal,"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n" +base.dists.normal.pdf,"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n" +base.dists.normal.quantile,"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n" +base.dists.normal.skewness,"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n" +base.dists.normal.stdev,"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n" +base.dists.normal.variance,"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n" +base.dists.pareto1.cdf,"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n" +base.dists.pareto1.entropy,"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n" +base.dists.pareto1.kurtosis,"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n" +base.dists.pareto1.logcdf,"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n" +base.dists.pareto1.logpdf,"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n" +base.dists.pareto1.mean,"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n" +base.dists.pareto1.median,"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n" +base.dists.pareto1.mode,"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n" +base.dists.pareto1.Pareto1,"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n" +base.dists.pareto1.pdf,"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n" +base.dists.pareto1.quantile,"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n" +base.dists.pareto1.skewness,"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n" +base.dists.pareto1.variance,"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n" +base.dists.poisson.cdf,"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\n\n// Negative mean parameter:\ny = base.dists.poisson.cdf( 2.0, -1.0 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n" +base.dists.poisson.entropy,"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n" +base.dists.poisson.kurtosis,"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n" +base.dists.poisson.logpmf,"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\n\n// Negative mean parameter:\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n" +base.dists.poisson.mean,"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n" +base.dists.poisson.median,"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n" +base.dists.poisson.mode,"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n" +base.dists.poisson.pmf,"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\n\n// Negative mean parameter:\ny = base.dists.poisson.pmf( 2.0, -0.5 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n" +base.dists.poisson.Poisson,"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n" +base.dists.poisson.quantile,"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\n\n// Negative mean parameter:\ny = base.dists.poisson.quantile( 2.0, -1.0 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n" +base.dists.poisson.skewness,"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n" +base.dists.poisson.stdev,"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n" +base.dists.poisson.variance,"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n" +base.dists.rayleigh.cdf,"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\n\n// Degenerate distribution when `sigma = 0.0`:\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n" +base.dists.rayleigh.entropy,"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n" +base.dists.rayleigh.kurtosis,"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n" +base.dists.rayleigh.logcdf,"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n" +base.dists.rayleigh.logpdf,"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n" +base.dists.rayleigh.mean,"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n" +base.dists.rayleigh.median,"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n" +base.dists.rayleigh.mgf,"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n" +base.dists.rayleigh.mode,"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n" +base.dists.rayleigh.pdf,"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\n\n// Degenerate distribution when `sigma = 0.0`:\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n" +base.dists.rayleigh.quantile,"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n" +base.dists.rayleigh.Rayleigh,"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n" +base.dists.rayleigh.skewness,"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n" +base.dists.rayleigh.stdev,"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n" +base.dists.rayleigh.variance,"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n" +base.dists.t.cdf,"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n" +base.dists.t.entropy,"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n" +base.dists.t.kurtosis,"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n" +base.dists.t.mean,"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n" +base.dists.t.median,"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n" +base.dists.t.mode,"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n" +base.dists.t.pdf,"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n" +base.dists.t.quantile,"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n" +base.dists.t.skewness,"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n" +base.dists.t.stdev,"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n" +base.dists.t.T,"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n" +base.dists.t.variance,"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n" +base.dists.triangular.cdf,"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n" +base.dists.triangular.entropy,"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n" +base.dists.triangular.kurtosis,"var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n" +base.dists.triangular.logcdf,"var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n" +base.dists.triangular.logpdf,"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n" +base.dists.triangular.mean,"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n" +base.dists.triangular.median,"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n" +base.dists.triangular.mgf,"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n" +base.dists.triangular.mode,"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n" +base.dists.triangular.pdf,"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n" +base.dists.triangular.quantile,"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n" +base.dists.triangular.skewness,"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n" +base.dists.triangular.stdev,"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n" +base.dists.triangular.Triangular,"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n" +base.dists.triangular.variance,"var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n" +base.dists.uniform.cdf,"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n" +base.dists.uniform.entropy,"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n" +base.dists.uniform.kurtosis,"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n" +base.dists.uniform.logcdf,"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n" +base.dists.uniform.logpdf,"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n" +base.dists.uniform.mean,"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n" +base.dists.uniform.median,"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n" +base.dists.uniform.mgf,"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n" +base.dists.uniform.pdf,"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n" +base.dists.uniform.quantile,"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n" +base.dists.uniform.skewness,"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n" +base.dists.uniform.stdev,"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n" +base.dists.uniform.Uniform,"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n" +base.dists.uniform.variance,"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n" +base.dists.weibull.cdf,"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n" +base.dists.weibull.entropy,"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n" +base.dists.weibull.kurtosis,"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n" +base.dists.weibull.logcdf,"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n" +base.dists.weibull.logpdf,"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n" +base.dists.weibull.mean,"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n" +base.dists.weibull.median,"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n" +base.dists.weibull.mgf,"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n" +base.dists.weibull.mode,"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n" +base.dists.weibull.pdf,"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n" +base.dists.weibull.quantile,"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n" +base.dists.weibull.skewness,"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n" +base.dists.weibull.stdev,"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n" +base.dists.weibull.variance,"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n" +base.dists.weibull.Weibull,"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n" +base.ellipe,"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n" +base.ellipk,"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n" +base.epsdiff,"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n\n// Custom scale function:\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n" +base.erf,"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n" +base.erfc,"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n" +base.erfcinv,"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n" +base.erfinv,"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n" +base.eta,"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n" +base.evalpoly,"var arr = [ 3.0, 2.0, 1.0 ];\n\n// 3*10^0 + 2*10^1 + 1*10^2\nvar v = base.evalpoly( arr, 10.0 )\n" +base.evalrational,"\n// 2x^3 + 4x^2 - 5x^1 - 6x^0\nvar P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n// 0.5x^1 + 3x^0\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n// Evaluate the rational function:\nvar v = base.evalrational( P, Q, 6.0 )\n" +base.exp,"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n" +base.exp2,"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n" +base.exp10,"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n" +base.expit,"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n" +base.expm1,"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n" +base.expm1rel,"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n" +base.exponent,"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n" +base.exponentf,"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n" +base.factorial,"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n" +base.factorialln,"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n" +base.fallingFactorial,"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n" +base.fibonacci,"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n" +base.fibonacciIndex,"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n" +base.fibpoly,"\n// 2^4 + 3*2^2 + 1\nvar v = base.fibpoly( 5, 2.0 )\n" +base.flipsign,"var z = base.flipsign( -3.14, 10.0 )\nz = base.flipsign( -3.14, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.14, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n" +base.float32ToInt32,"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n" +base.float32ToUint32,"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n" +base.float64ToFloat32,"var y = base.float64ToFloat32( 1.337 )\n" +base.float64ToInt32,"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n" +base.float64ToUint32,"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n" +base.floor,"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n" +base.floor2,"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n" +base.floor10,"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n" +base.floorb,"\n// Round to 4 decimal places:\nvar y = base.floorb( 3.14159, -4, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.floorb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two toward negative infinity:\ny = base.floorb( 5.0, 1, 2 )\n" +base.floorn,"\n// Round to 4 decimal places:\nvar y = base.floorn( 3.14159, -4 )\n\n// If `n = 0`, standard round toward negative infinity behavior:\ny = base.floorn( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.floorn( 12368.0, 3 )\n" +base.floorsd,"var y = base.floorsd( 3.14159, 5 )\ny = base.floorsd( 3.14159, 1 )\ny = base.floorsd( 12368.0, 2 )\ny = base.floorsd( 0.0313, 2, 2 )\n" +base.fresnel,"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.fresnel( out, 0.0 )\nvar bool = ( v === out )\n" +base.fresnelc,"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n" +base.fresnels,"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n" +base.frexp,"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar y = base.frexp( out, 4.0 )\nvar bool = ( y === out )\n" +base.fromBinaryString,"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\n\n// The function handles subnormals:\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\n\n// The function handles special values:\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n" +base.fromBinaryStringf,"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\n\n// The function handles subnormals:\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\n\n// The function handles special values:\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n" +base.fromBinaryStringUint8,"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n" +base.fromBinaryStringUint16,"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n" +base.fromBinaryStringUint32,"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n" +base.fromWordf,"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n" +base.fromWords,"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n" +base.gamma,"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n" +base.gamma1pm1,"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n" +base.gammaDeltaRatio,"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n" +base.gammainc,"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n" +base.gammaincinv,"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n" +base.gammaLanczosSum,"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n" +base.gammaLanczosSumExpGScaled,"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n" +base.gammaln,"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n" +base.gasum,"\n// Standard usage:\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar sum = base.gasum( x.length, x, 1 )\n\n// Sum every other value:\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nsum = base.gasum( N, x, stride )\n\n// Use view offset; e.g., starting at 2nd element:\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nsum = base.gasum( N, x1, stride )\n" +base.gaxpy,"\n// Standard usage:\nvar x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nvar alpha = 5.0;\nbase.gaxpy( x.length, alpha, x, 1, y, 1 )\n\n// Using `N` and `stride` parameters:\nvar N = base.floor( x.length / 2 );\nbase.gaxpy( N, alpha, x, 2, y, -1 )\n\n// Using view offsets:\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.gaxpy( N, 5.0, x1, -2, y1, 1 )\ny0\n" +base.gcd,"var v = base.gcd( 48, 18 )\n" +base.gcopy,"\n// Standard usage:\nvar x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.gcopy( x.length, x, 1, y, 1 )\n\n// Advanced indexing:\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nvar N = base.floor( x.length / 2 );\nbase.gcopy( N, x, -2, y, 1 )\n\n// Using typed array views:\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.gcopy( N, x1, -2, y1, 1 )\ny0\n" +base.getHighWord,"var w = base.getHighWord( 3.14e201 )\n" +base.getLowWord,"var w = base.getLowWord( 3.14e201 )\n" +base.hacovercos,"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n" +base.hacoversin,"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n" +base.havercos,"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n" +base.haversin,"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n" +base.heaviside,"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n" +base.hermitepoly,"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n" +base.hypot,"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n" +base.imul,"var v = base.imul( -10|0, 4|0 )\n" +base.imuldw,"var v = base.imuldw( 1, 10 )\n" +base.int32ToUint32,"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n" +base.inv,"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n" +base.isEven,"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n" +base.isEvenInt32,"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n" +base.isFinite,"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n" +base.isInfinite,"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n" +base.isInteger,"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n" +base.isnan,"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n" +base.isNegativeInteger,"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n" +base.isNegativeZero,"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n" +base.isNonNegativeInteger,"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n" +base.isNonPositiveInteger,"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n" +base.isOdd,"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n" +base.isOddInt32,"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n" +base.isPositiveInteger,"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n" +base.isPositiveZero,"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n" +base.isPow2Uint32,"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n" +base.isProbability,"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n" +base.isSafeInteger,"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n" +base.kernelBetainc,"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\nout = new Array( 2 );\nvar v = base.kernelBetainc( out, 0.2, 1.0, 2.0, true, true )\nvar bool = ( v === out )\n" +base.kernelBetaincinv,"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n" +base.kernelCos,"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n" +base.kernelSin,"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n" +base.kernelTan,"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n" +base.kroneckerDelta,"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n" +base.lcm,"var v = base.lcm( 21, 6 )\n" +base.ldexp,"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n" +base.ln,"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n" +base.log,"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n" +base.log1mexp,"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n" +base.log1p,"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n" +base.log1pexp,"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n" +base.log2,"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n" +base.log10,"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n" +base.logaddexp,"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n" +base.logit,"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n" +base.lucas,"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n" +base.lucaspoly,"\n// 2^5 + 5*2^3 + 5*2\nvar v = base.lucaspoly( 5, 2.0 )\n" +base.max,"var v = base.max( 3.14, 4.2 )\nv = base.max( 5.9, 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n" +base.maxabs,"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 5.9, 3.14, 4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n" +base.min,"var v = base.min( 3.14, 4.2 )\nv = base.min( 5.9, 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n" +base.minabs,"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 5.9, 3.14, 4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n" +base.minmax,"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 5.9, 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\nv = base.minmax( 3.14 )\nvar out = new Array( 2 );\nv = base.minmax( out, 3.14 )\nvar bool = ( v === out )\n" +base.minmaxabs,"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14, 4.2 )\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\nv = base.minmaxabs( 3.14 )\nvar out = new Array( 2 );\nv = base.minmaxabs( out, 3.14 )\nvar bool = ( v === out )\n" +base.modf,"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n\n// Provide an output array:\nvar out = new Float64Array( 2 );\nparts = base.modf( out, 3.14 )\nvar bool = ( parts === out )\n" +base.ndarray,"var ctor = base.ndarray( 'float64', 3 )\n\n// To create a new instance...\nvar b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nvar v = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99 );\narr.get( 1, 1 )\n" +base.ndarrayMemoized,"var ctor = base.ndarrayMemoized( 'float64', 3 )\nvar f = base.ndarrayMemoized( 'float64', 3 )\nvar bool = ( f === ctor )\n\n// To create a new instance...\nvar b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nvar v = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99 );\narr.get( 1, 1 )\n" +base.negafibonacci,"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n" +base.negalucas,"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n" +base.nonfibonacci,"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n" +base.normalize,"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n\n// Special cases:\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.normalize( out, 3.14e-319 )\nbool = ( v === out )\n" +base.normalizef,"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n\n// Special cases:\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n\n// Provide an output array:\nout = new Float32Array( 2 );\nvar v = base.normalizef( out, base.float64ToFloat32( 1.401e-45 ) )\nbool = ( v === out )\n" +base.normhermitepoly,"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n" +base.pdiff,"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n" +base.polygamma,"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n" +base.pow,"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n" +base.powm1,"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n" +base.rad2deg,"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\n\n// Due to finite precision, canonical values may not be returned:\nd = base.rad2deg( PI/6.0 )\n" +base.ramp,"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n" +base.random.arcsine,"var r = base.random.arcsine( 2.0, 5.0 )\n" +base.random.bernoulli,"var r = base.random.bernoulli( 0.8 );\n" +base.random.beta,"var r = base.random.beta( 2.0, 5.0 );\n" +base.random.betaprime,"var r = base.random.betaprime( 2.0, 5.0 );\n" +base.random.binomial,"var r = base.random.binomial( 20, 0.8 );\n" +base.random.boxMuller,"var r = base.random.boxMuller();\n" +base.random.cauchy,"var r = base.random.cauchy( 2.0, 5.0 );\n" +base.random.chi,"var r = base.random.chi( 2 );\n" +base.random.chisquare,"var r = base.random.chisquare( 2 );\n" +base.random.cosine,"var r = base.random.cosine( 2.0, 5.0 );\n" +base.random.discreteUniform,"var r = base.random.discreteUniform( 2, 50 );\n" +base.random.erlang,"var r = base.random.erlang( 2, 5.0 );\n" +base.random.exponential,"var r = base.random.exponential( 7.9 );\n" +base.random.f,"var r = base.random.f( 2.0, 5.0 );\n" +base.random.frechet,"var r = base.random.frechet( 2.0, 5.0, 3.33 );\n" +base.random.gamma,"var r = base.random.gamma( 2.0, 5.0 );\n" +base.random.geometric,"var r = base.random.geometric( 0.8 );\n" +base.random.gumbel,"var r = base.random.gumbel( 2.0, 5.0 );\n" +base.random.hypergeometric,"var r = base.random.hypergeometric( 20, 10, 7 );\n" +base.random.improvedZiggurat,"var r = base.random.improvedZiggurat();\n" +base.random.invgamma,"var r = base.random.invgamma( 2.0, 5.0 );\n" +base.random.kumaraswamy,"var r = base.random.kumaraswamy( 2.0, 5.0 );\n" +base.random.laplace,"var r = base.random.laplace( 2.0, 5.0 );\n" +base.random.levy,"var r = base.random.levy( 2.0, 5.0 );\n" +base.random.logistic,"var r = base.random.logistic( 2.0, 5.0 );\n" +base.random.lognormal,"var r = base.random.lognormal( 2.0, 5.0 );\n" +base.random.minstd,"var r = base.random.minstd();\n" +base.random.minstdShuffle,"var r = base.random.minstdShuffle();\n" +base.random.mt19937,"var r = base.random.mt19937();\n" +base.random.negativeBinomial,"var r = base.random.negativeBinomial( 20, 0.8 );\n" +base.random.normal,"var r = base.random.normal( 2.0, 5.0 );\n" +base.random.pareto1,"var r = base.random.pareto1( 2.0, 5.0 );\n" +base.random.poisson,"var r = base.random.poisson( 7.9 );\n" +base.random.randi,"var r = base.random.randi();\n" +base.random.randn,"var r = base.random.randn();\n" +base.random.randu,"var r = base.random.randu();\n" +base.random.rayleigh,"var r = base.random.rayleigh( 2.5 );\n" +base.random.t,"var r = base.random.t( 2.0 );\n" +base.random.triangular,"var r = base.random.triangular( 2.0, 5.0, 3.33 );\n" +base.random.uniform,"var r = base.random.uniform( 2.0, 5.0 );\n" +base.random.weibull,"var r = base.random.weibull( 2.0, 5.0 );\n" +base.reldiff,"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\n\n// Custom scale function:\nfunction scale( x, y ) {\n var s;\n ...\n x = base.abs( x );\n y = base.abs( y );\n ...\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n ...\n // Scale in units of epsilon:\n return s * EPS;\n};\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n" +base.rempio2,"var y = new Array( 2 );\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n" +base.risingFactorial,"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n" +base.rotl32,"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n" +base.rotr32,"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n" +base.round,"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n" +base.round2,"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n" +base.round10,"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n" +base.roundb,"\n// Round to 2 decimal places:\nvar y = base.roundb( 3.14159, -2, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.roundb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two:\ny = base.roundb( 5.0, 1, 2 )\n" +base.roundn,"\n// Round to 2 decimal places:\nvar y = base.roundn( 3.14159, -2 )\n\n// If `n = 0`, standard round behavior:\ny = base.roundn( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.roundn( 12368.0, 3 )\n" +base.roundsd,"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n" +base.rsqrt,"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n" +base.sasum,"\n// Standard usage:\nvar x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\nvar sum = base.sasum( x.length, x, 1 )\n\n// Sum every other value:\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nsum = base.sasum( N, x, stride )\n\n// Use view offset; e.g., starting at 2nd element:\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nsum = base.sasum( N, x1, stride )\n" +base.saxpy,"\n// Standard usage:\nvar x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.saxpy( x.length, alpha, x, 1, y, 1 )\n\n// Using `N` and `stride` parameters:\nvar N = base.floor( x.length / 2 );\nbase.saxpy( N, alpha, x, 2, y, -1 )\n\n// Using view offsets:\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.saxpy( N, 5.0, x1, -2, y1, 1 )\ny0\n" +base.scopy,"\n// Standard usage:\nvar x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.scopy( x.length, x, 1, y, 1 )\n\n// Advanced indexing:\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.scopy( N, x, -2, y, 1 )\n\n// Using typed array views:\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.scopy( N, x1, -2, y1, 1 )\ny0\n" +base.setHighWord,"\n// Set the higher order bits of `+infinity` to return `1`:\nvar high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n" +base.setLowWord,"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\n\n// Special cases:\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n" +base.sici,"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n\n// Provide an output array:\nvar out = new Float64Array( 2 );\ny = base.sici( out, 3.0 )\nvar bool = ( y === out )\n" +base.signbit,"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n" +base.signbitf,"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n" +base.significandf,"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n" +base.signum,"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n" +base.sin,"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n" +base.sinc,"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n" +base.sincos,"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincos( out, 0.0 )\nvar bool = ( v === out )\n" +base.sincospi,"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincospi( out, 0.0 )\nvar bool = ( v === out )\n" +base.sinh,"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n" +base.sinpi,"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n" +base.spence,"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n" +base.sqrt,"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n" +base.sqrt1pm1,"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n" +base.sumSeries,"\n// Using an ES6 generator function:\nfunction* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n};\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\n\n// Using a closure:\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n};\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\n\n// Setting an initial value for the sum:\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n\n// Changing the maximum number of terms to be summed:\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n\n// Adjusting the used tolerance:\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n" +base.tan,"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n" +base.tanh,"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n" +base.toBinaryString,"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n" +base.toBinaryStringf,"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n" +base.toBinaryStringUint8,"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n" +base.toBinaryStringUint16,"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n" +base.toBinaryStringUint32,"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n" +base.toWordf,"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n" +base.toWords,"var w = base.toWords( 3.14e201 )\n\n// Provide an output array:\nvar out = new Uint32Array( 2 );\nw = base.toWords( out, 3.14e201 )\nvar bool = ( w === out )\n" +base.trigamma,"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n" +base.trunc,"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n" +base.trunc2,"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n" +base.trunc10,"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n" +base.truncb,"\n// Round to 4 decimal places:\nvar y = base.truncb( 3.14159, -4, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.truncb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two toward zero:\ny = base.truncb( 5.0, 1, 2 )\n" +base.truncn,"\n// Round to 4 decimal places:\nvar y = base.truncn( 3.14159, -4 )\n\n// If `n = 0`, standard round behavior:\ny = base.truncn( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.truncn( 12368.0, 3 )\n" +base.truncsd,"var y = base.truncsd( 3.14159, 5 )\ny = base.truncsd( 3.14159, 1 )\ny = base.truncsd( 12368.0, 2 )\ny = base.truncsd( 0.0313, 2, 2 )\n" +base.uimul,"var v = base.uimul( 10>>>0, 4>>>0 )\n" +base.uimuldw,"var v = base.uimuldw( 1, 10 )\n" +base.uint32ToInt32,"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n" +base.vercos,"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n" +base.versin,"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n" +base.wrap,"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n" +base.xlog1py,"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n" +base.xlogy,"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n" +base.zeta,"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\n\n// Evaluate at a pole:\ny = base.zeta( 1.0 )\n" +BERNDT_CPS_WAGES_1985,"var data = BERNDT_CPS_WAGES_1985()\n" +bifurcate,"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\n\n// Output group results as indices:\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\n\n// Output group results as index-element pairs:\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n" +bifurcateBy,"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\n\n// Output group results as indices:\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n" +bifurcateByAsync,"\n// Basic usage:\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\n\n// Output group results as indices:\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n" +bifurcateIn,"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\n\n// Output group results as keys:\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n" +bifurcateOwn,"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\n\n// Output group results as keys:\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n" +binomialTest,"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n})\n" +Buffer,"var b = new Buffer( 4 )\n" +buffer2json,"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n" +capitalize,"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n" +capitalizeKeys,"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n" +CATALAN,"CATALAN\n" +CBRT_EPS,"CBRT_EPS\n" +chdir,"var err = chdir( '/path/to/current/working/directory' )\n" +chi2gof,"\n// Provide expected probabilities...\nvar x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p )\nout.print()\n\n// Set significance level...\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.print()\n\n// Calculate the test p-value via Monte Carlo simulation...\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts )\n\n// Verify that data comes from Poisson distribution...\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n// Generate a frequency table...\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda )\n" +circarray2iterator,"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n" +circularArrayStream,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +CircularBuffer,"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n" +CMUDICT,"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n" +complex,"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n" +Complex64,"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n" +COMPLEX64_NUM_BYTES,"COMPLEX64_NUM_BYTES\n" +Complex128,"var z = new Complex128( 5.0, 3.0 )\nz.re\nz.im\n" +COMPLEX128_NUM_BYTES,"COMPLEX128_NUM_BYTES\n" +compose,"function a( x ) {\n return 2 * x;\n}\nfunction b( x ) {\n return x + 3;\n}\nfunction c( x ) {\n return x / 5;\n}\nvar f = compose( c, b, a );\nvar z = f( 6 )\n" +composeAsync,"function a( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, 2*x );\n }\n};\nfunction b( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x+3 );\n }\n};\nfunction c( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x/5 );\n }\n};\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nf( 6, done )\n" +configdir,"var dir = configdir()\ndir = configdir( 'appname/config' )\n" +conj,"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n" +constantFunction,"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n" +constantStream,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +constructorName,"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n" +contains,"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\n\n// Supply a position:\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n" +convertArray,"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n" +convertArraySame,"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n" +convertPath,"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\foo\\bar\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\foo\\bar\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\foo\\bar\\beep.c', 'posix' )\n" +copy,"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\n\n// Set the `level` option to limit the copy depth:\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n" +copyBuffer,"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n" +countBy,"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n" +countByAsync,"\n// Basic usage:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\n\n// Limit number of concurrent invocations:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n\n// Process sequentially:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n" +curry,"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\n\n// Supply arity:\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\n\n// Provide function context:\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n};\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n" +curryRight,"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\n\n// Supply arity:\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\n\n// Provide function context:\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n};\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n" +cwd,"var dir = cwd()\n" +DALE_CHALL_NEW,"var list = DALE_CHALL_NEW()\n" +datasets,"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n" +dayOfQuarter,"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\n\n// Other ways to supply month:\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n" +dayOfYear,"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\n\n// Other ways to supply month:\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n" +daysInMonth,"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n" +daysInYear,"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n" +debugSinkStream,"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n" +debugStream,"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n" +deepEqual,"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n" +deepGet,"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\n\n// Specify a custom separator via the `sep` option:\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n" +deepHasOwnProp,"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\n\n// Specify a custom separator via the `sep` option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n" +deepHasProp,"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\n\n// Specify a custom separator via the `sep` option:\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n" +deepPluck,"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n];\nout = deepPluck( arr, [ 'a', 1 ] )\n" +deepSet,"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj, 'a.b.c', 'beep' )\n\n// Specify an alternative separator via the sep option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\n\n// To create a key path which does not exist, set the create option to true:\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n" +defineMemoizedProperty,"var obj = {};\nfunction foo() {\n return 'bar';\n};\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n});\nobj.foo\n" +defineProperties,"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n});\nobj.foo\nobj.baz\n" +defineProperty,"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n});\nobj.foo = 'boop';\nobj\n" +dirname,"var dir = dirname( './foo/bar/index.js' )\n" +DoublyLinkedList,"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n" +doUntil,"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n" +doUntilAsync,"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\ndoUntilAsync( fcn, predicate, done )\n" +doUntilEach,"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n" +doUntilEachRight,"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n" +doWhile,"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n" +doWhileAsync,"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\ndoWhileAsync( fcn, predicate, done )\n" +doWhileEach,"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n" +doWhileEachRight,"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n" +E,"E\n" +emptyStream,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +endsWith,"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n" +enumerableProperties,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n" +enumerablePropertiesIn,"var props = enumerablePropertiesIn( [] )\n" +enumerablePropertySymbols,"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n" +enumerablePropertySymbolsIn,"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n" +ENV,"var user = ENV.USER\n" +EPS,"EPS\n" +error2json,"var err = new Error( 'beep' );\nvar json = error2json( err )\n" +EULERGAMMA,"EULERGAMMA\n" +every,"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n" +everyBy,"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n" +everyByAsync,"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n" +everyByRight,"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n" +everyByRightAsync,"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n" +evil,"var v = evil( '5*4*3*2*1' )\n" +exists,"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n" +expandContractions,"var str = 'I won\'t be able to get y\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\'t to be my fault, because, you know, I didn\'t know';\nout = expandContractions( str )\n" +extname,"var ext = extname( 'index.js' )\n" +fastmath.abs,"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n" +fastmath.acosh,"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\n\n// The function overflows for large `x`:\nv = fastmath.acosh( 1.0e308 )\n" +fastmath.ampbm,"var h = fastmath.ampbm( 5.0, 12.0 )\n" +fastmath.asinh,"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\n\n// The function overflows for large `x`:\nv = fastmath.asinh( 1.0e200 )\n\n// The function underflows for small `x`:\nv = fastmath.asinh( 1.0e-50 )\n" +fastmath.atanh,"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\n\n// The function underflows for small `x`:\nv = fastmath.atanh( 1.0e-17 )\n" +fastmath.hypot,"var h = fastmath.hypot( -5.0, 12.0 )\n\n// For a sufficiently large `x` and/or `y`, the function overflows:\nh = fastmath.hypot( 1.0e154, 1.0e154 )\n\n// For sufficiently small `x` and/or `y`, the function underflows:\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n" +fastmath.log2Uint32,"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n" +fastmath.max,"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n" +fastmath.min,"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n" +fastmath.powint,"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n" +fastmath.sqrtUint32,"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n" +FEMALE_FIRST_NAMES_EN,"var list = FEMALE_FIRST_NAMES_EN()\n" +FIFO,"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n" +find,"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\n\n// Limit number of results:\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\n\n// Return both indices and values as index-value pairs:\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n" +flattenArray,"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\n\n// Set the maximum depth:\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n\n// Deep copy:\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n" +flattenObject,"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\n\n// Set the `depth` option to flatten to a specified depth:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\n\n// Set the `delimiter` option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\n\n// Flatten arrays:\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n" +flignerTest,"\n// Data from Hollander & Wolfe (1973), p. 116:\nvar x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n];\nout = flignerTest( arr, { 'groups': groups })\n" +FLOAT16_CBRT_EPS,"FLOAT16_CBRT_EPS\n" +FLOAT16_EPS,"FLOAT16_EPS\n" +FLOAT16_EXPONENT_BIAS,"FLOAT16_EXPONENT_BIAS\n" +FLOAT16_MAX,"FLOAT16_MAX\n" +FLOAT16_MAX_SAFE_INTEGER,"FLOAT16_MAX_SAFE_INTEGER\n" +FLOAT16_MIN_SAFE_INTEGER,"FLOAT16_MIN_SAFE_INTEGER\n" +FLOAT16_NINF,"FLOAT16_NINF\n" +FLOAT16_NUM_BYTES,"FLOAT16_NUM_BYTES\n" +FLOAT16_PINF,"FLOAT16_PINF\n" +FLOAT16_PRECISION,"FLOAT16_PRECISION\n" +FLOAT16_SMALLEST_NORMAL,"FLOAT16_SMALLEST_NORMAL\n" +FLOAT16_SMALLEST_SUBNORMAL,"FLOAT16_SMALLEST_SUBNORMAL\n" +FLOAT16_SQRT_EPS,"FLOAT16_SQRT_EPS\n" +FLOAT32_CBRT_EPS,"FLOAT32_CBRT_EPS\n" +FLOAT32_EPS,"FLOAT32_EPS\n" +FLOAT32_EXPONENT_BIAS,"FLOAT32_EXPONENT_BIAS\n" +FLOAT32_MAX,"FLOAT32_MAX\n" +FLOAT32_MAX_SAFE_INTEGER,"FLOAT32_MAX_SAFE_INTEGER\n" +FLOAT32_MIN_SAFE_INTEGER,"FLOAT32_MIN_SAFE_INTEGER\n" +FLOAT32_NINF,"FLOAT32_NINF\n" +FLOAT32_NUM_BYTES,"FLOAT32_NUM_BYTES\n" +FLOAT32_PINF,"FLOAT32_PINF\n" +FLOAT32_PRECISION,"FLOAT32_PRECISION\n" +FLOAT32_SMALLEST_NORMAL,"FLOAT32_SMALLEST_NORMAL\n" +FLOAT32_SMALLEST_SUBNORMAL,"FLOAT32_SMALLEST_SUBNORMAL\n" +FLOAT32_SQRT_EPS,"FLOAT32_SQRT_EPS\n" +Float32Array,"var arr = new Float32Array()\n" +FLOAT64_EXPONENT_BIAS,"FLOAT64_EXPONENT_BIAS\n" +FLOAT64_HIGH_WORD_EXPONENT_MASK,"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n" +FLOAT64_HIGH_WORD_SIGNIFICAND_MASK,"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n" +FLOAT64_MAX,"FLOAT64_MAX\n" +FLOAT64_MAX_BASE2_EXPONENT,"FLOAT64_MAX_BASE2_EXPONENT\n" +FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL,"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n" +FLOAT64_MAX_BASE10_EXPONENT,"FLOAT64_MAX_BASE10_EXPONENT\n" +FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL,"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n" +FLOAT64_MAX_LN,"FLOAT64_MAX_LN\n" +FLOAT64_MAX_SAFE_FIBONACCI,"FLOAT64_MAX_SAFE_FIBONACCI\n" +FLOAT64_MAX_SAFE_INTEGER,"FLOAT64_MAX_SAFE_INTEGER\n" +FLOAT64_MAX_SAFE_LUCAS,"FLOAT64_MAX_SAFE_LUCAS\n" +FLOAT64_MAX_SAFE_NTH_FIBONACCI,"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n" +FLOAT64_MAX_SAFE_NTH_LUCAS,"FLOAT64_MAX_SAFE_NTH_LUCAS\n" +FLOAT64_MIN_BASE2_EXPONENT,"FLOAT64_MIN_BASE2_EXPONENT\n" +FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL,"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n" +FLOAT64_MIN_BASE10_EXPONENT,"FLOAT64_MIN_BASE10_EXPONENT\n" +FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL,"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n" +FLOAT64_MIN_LN,"FLOAT64_MIN_LN\n" +FLOAT64_MIN_SAFE_INTEGER,"FLOAT64_MIN_SAFE_INTEGER\n" +FLOAT64_NUM_BYTES,"FLOAT64_NUM_BYTES\n" +FLOAT64_PRECISION,"FLOAT64_PRECISION\n" +FLOAT64_SMALLEST_NORMAL,"FLOAT64_SMALLEST_NORMAL\n" +FLOAT64_SMALLEST_SUBNORMAL,"FLOAT64_SMALLEST_SUBNORMAL\n" +Float64Array,"var arr = new Float64Array()\n" +forEach,"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n" +forEachAsync,"\n// Basic usage:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\n\n// Limit number of concurrent invocations:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n\n// Process sequentially:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n" +forEachRight,"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n" +forEachRightAsync,"\n// Basic usage:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\n\n// Limit number of concurrent invocations:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n\n// Process sequentially:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n" +forIn,"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n" +forOwn,"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n" +FOURTH_PI,"FOURTH_PI\n" +FOURTH_ROOT_EPS,"FOURTH_ROOT_EPS\n" +FRB_SF_WAGE_RIGIDITY,"var data = FRB_SF_WAGE_RIGIDITY()\n" +fromCodePoint,"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n" +functionName,"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n" +functionSequence,"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n" +functionSequenceAsync,"function a( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, 2*x );\n }\n};\nfunction b( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x+3 );\n }\n};\nfunction c( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x/5 );\n }\n};\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nf( 6, done )\n" +GAMMA_LANCZOS_G,"GAMMA_LANCZOS_G\n" +getegid,"var gid = getegid()\n" +geteuid,"var uid = geteuid()\n" +getgid,"var gid = getgid()\n" +getGlobal,"var g = getGlobal()\n" +getPrototypeOf,"var proto = getPrototypeOf( {} )\n" +getuid,"var uid = getuid()\n" +GLAISHER,"GLAISHER\n" +group,"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\n\n// Output group results as indices:\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\n\n// Output group results as index-element pairs:\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n" +groupBy,"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\n\n// Output group results as indices:\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n" +groupByAsync,"\n// Basic usage:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\n\n// Output group results as indices:\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\n\n// Limit number of concurrent invocations:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n\n// Process sequentially:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n" +groupIn,"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\n\n// Output group results as keys:\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n" +groupOwn,"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\n\n// Output group results as keys:\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n" +HALF_LN2,"HALF_LN2\n" +HALF_PI,"HALF_PI\n" +HARRISON_BOSTON_HOUSE_PRICES,"var data = HARRISON_BOSTON_HOUSE_PRICES()\n" +HARRISON_BOSTON_HOUSE_PRICES_CORRECTED,"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n" +hasArrayBufferSupport,"var bool = hasArrayBufferSupport()\n" +hasAsyncAwaitSupport,"var bool = hasAsyncAwaitSupport()\n" +hasAsyncIteratorSymbolSupport,"var bool = hasAsyncIteratorSymbolSupport()\n" +hasClassSupport,"var bool = hasClassSupport()\n" +hasDefinePropertiesSupport,"var bool = hasDefinePropertiesSupport()\n" +hasDefinePropertySupport,"var bool = hasDefinePropertySupport()\n" +hasFloat32ArraySupport,"var bool = hasFloat32ArraySupport()\n" +hasFloat64ArraySupport,"var bool = hasFloat64ArraySupport()\n" +hasFunctionNameSupport,"var bool = hasFunctionNameSupport()\n" +hasGeneratorSupport,"var bool = hasGeneratorSupport()\n" +hasInt8ArraySupport,"var bool = hasInt8ArraySupport()\n" +hasInt16ArraySupport,"var bool = hasInt16ArraySupport()\n" +hasInt32ArraySupport,"var bool = hasInt32ArraySupport()\n" +hasIteratorSymbolSupport,"var bool = hasIteratorSymbolSupport()\n" +hasMapSupport,"var bool = hasMapSupport()\n" +hasNodeBufferSupport,"var bool = hasNodeBufferSupport()\n" +hasOwnProp,"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n" +hasProp,"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n" +hasProxySupport,"var bool = hasProxySupport()\n" +hasSetSupport,"var bool = hasSetSupport()\n" +hasSharedArrayBufferSupport,"var bool = hasSharedArrayBufferSupport()\n" +hasSymbolSupport,"var bool = hasSymbolSupport()\n" +hasToStringTagSupport,"var bool = hasToStringTagSupport()\n" +hasUint8ArraySupport,"var bool = hasUint8ArraySupport()\n" +hasUint8ClampedArraySupport,"var bool = hasUint8ClampedArraySupport()\n" +hasUint16ArraySupport,"var bool = hasUint16ArraySupport()\n" +hasUint32ArraySupport,"var bool = hasUint32ArraySupport()\n" +hasWeakMapSupport,"var bool = hasWeakMapSupport()\n" +hasWeakSetSupport,"var bool = hasWeakSetSupport()\n" +hasWebAssemblySupport,"var bool = hasWebAssemblySupport()\n" +HERNDON_VENUS_SEMIDIAMETERS,"var d = HERNDON_VENUS_SEMIDIAMETERS()\n" +homedir,"var home = homedir()\n" +HOURS_IN_DAY,"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n" +HOURS_IN_WEEK,"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n" +hoursInMonth,"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n" +hoursInYear,"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n" +httpServer,"\n// Basic usage:\nvar createServer = httpServer()\n\n// Provide a request callback:\nfunction onRequest( request, response ) {\n console.log( request.url );\n response.end( 'OK' );\n};\ncreateServer = httpServer( onRequest )\n\n// Specify a specific port:\nvar opts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n" +identity,"var v = identity( 3.14 )\n" +ifelse,"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n" +ifelseAsync,"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nifelseAsync( predicate, 'beep', 'boop', done )\n" +ifthen,"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n" +ifthenAsync,"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n};\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n};\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nifthenAsync( predicate, x, y, done )\n" +imag,"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n" +IMG_ACANTHUS_MOLLIS,"var img = IMG_ACANTHUS_MOLLIS()\n" +IMG_AIRPLANE_FROM_ABOVE,"var img = IMG_AIRPLANE_FROM_ABOVE()\n" +IMG_ALLIUM_OREOPHILUM,"var img = IMG_ALLIUM_OREOPHILUM()\n" +IMG_BLACK_CANYON,"var img = IMG_BLACK_CANYON()\n" +IMG_DUST_BOWL_HOME,"var img = IMG_DUST_BOWL_HOME()\n" +IMG_FRENCH_ALPINE_LANDSCAPE,"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n" +IMG_LOCOMOTION_HOUSE_CAT,"var img = IMG_LOCOMOTION_HOUSE_CAT()\n" +IMG_LOCOMOTION_NUDE_MALE,"var img = IMG_LOCOMOTION_NUDE_MALE()\n" +IMG_MARCH_PASTORAL,"var img = IMG_MARCH_PASTORAL()\n" +IMG_NAGASAKI_BOATS,"var img = IMG_NAGASAKI_BOATS()\n" +incrapcorr,"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n" +incrcount,"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n" +incrcovariance,"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n" +incrcovmat,"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar vec = ndarray( 'float64', 1 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n" +incrcv,"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n" +increwmean,"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n" +increwstdev,"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n" +increwvariance,"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n" +incrgmean,"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n" +incrgrubbs,"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n};\nres.print()\n" +incrhmean,"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n" +incrkmeans,"var accumulator = incrkmeans( 5, 2 );\nvar vec = ndarray( 'float64', 1 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n" +incrkurtosis,"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n" +incrmaape,"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n" +incrmae,"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n" +incrmapcorr,"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n" +incrmape,"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n" +incrmax,"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n" +incrmaxabs,"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n" +incrmcovariance,"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n" +incrmcv,"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n" +incrmda,"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n" +incrme,"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n" +incrmean,"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n" +incrmeanabs,"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n" +incrmeanabs2,"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n" +incrmeanstdev,"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n" +incrmeanvar,"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n" +incrmgmean,"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n" +incrmgrubbs,"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n};\nres.print()\n" +incrmhmean,"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n" +incrmidrange,"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n" +incrmin,"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n" +incrminabs,"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n" +incrminmax,"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n" +incrminmaxabs,"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n" +incrmmaape,"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n" +incrmmae,"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n" +incrmmape,"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n" +incrmmax,"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n" +incrmmaxabs,"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n" +incrmmda,"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n" +incrmme,"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n" +incrmmean,"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n" +incrmmeanabs,"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n" +incrmmeanabs2,"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n" +incrmmeanstdev,"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n" +incrmmeanvar,"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n" +incrmmidrange,"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n" +incrmmin,"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n" +incrmminabs,"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n" +incrmminmax,"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n" +incrmminmaxabs,"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n" +incrmmpe,"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n" +incrmmse,"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n" +incrmpcorr,"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n" +incrmpcorr2,"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n" +incrmpcorrdist,"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n" +incrmpe,"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n" +incrmprod,"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n" +incrmrange,"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n" +incrmrmse,"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n" +incrmrss,"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n" +incrmse,"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n" +incrmstdev,"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n" +incrmsum,"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n" +incrmsumabs,"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n" +incrmsumabs2,"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n" +incrmsummary,"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n" +incrmsumprod,"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n" +incrmvariance,"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n" +incrmvmr,"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n" +incrpcorr,"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n" +incrpcorr2,"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n" +incrpcorrdist,"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n" +incrpcorrdistmat,"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar vec = ndarray( 'float64', 1 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n" +incrpcorrmat,"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar vec = ndarray( 'float64', 1 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n" +incrprod,"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n" +incrrange,"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n" +incrrmse,"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n" +incrrss,"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n" +incrskewness,"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n" +incrspace,"var arr = incrspace( 0, 11, 2 )\n" +incrstdev,"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n" +incrsum,"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n" +incrsumabs,"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n" +incrsumabs2,"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n" +incrsummary,"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n" +incrsumprod,"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n" +incrvariance,"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n" +incrvmr,"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n" +incrwmean,"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n" +ind2sub,"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n\n// Provide an output array:\nvar out = new Array( d.length );\ns = ind2sub( out, d, 17 )\nvar bool = ( s === out )\n" +indexOf,"\n// Basic usage:\nvar arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\n\n// Using a `fromIndex`:\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\n\n// `fromIndex` which exceeds `array` length:\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\n\n// Negative `fromIndex`:\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\n\n// Negative `fromIndex` exceeding input `array` length:\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\n\n// Array-like objects:\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n" +inherit,"\n// Create a parent constructor:\nfunction Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\n\n// Create a child constructor:\nfunction Bar() { Foo.call( this ); return this; };\n\n// Setup inheritance:\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n" +inheritedEnumerableProperties,"var props = inheritedEnumerableProperties( {} )\n" +inheritedEnumerablePropertySymbols,"var symbols = inheritedEnumerablePropertySymbols( [] )\n" +inheritedKeys,"var keys = inheritedKeys( {} )\n" +inheritedNonEnumerableProperties,"var props = inheritedNonEnumerableProperties( {} )\n" +inheritedNonEnumerablePropertyNames,"var keys = inheritedNonEnumerablePropertyNames( {} )\n" +inheritedNonEnumerablePropertySymbols,"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n" +inheritedProperties,"var symbols = inheritedProperties( [] )\n" +inheritedPropertyDescriptor,"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n" +inheritedPropertyDescriptors,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n" +inheritedPropertyNames,"var keys = inheritedPropertyNames( [] )\n" +inheritedPropertySymbols,"var symbols = inheritedPropertySymbols( [] )\n" +inheritedWritableProperties,"var props = inheritedWritableProperties( {} )\n" +inheritedWritablePropertyNames,"var keys = inheritedWritablePropertyNames( {} )\n" +inheritedWritablePropertySymbols,"var symbols = inheritedWritablePropertySymbols( [] )\n" +inmap,"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n" +inmapAsync,"\n// Basic usage:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n\n// Process sequentially:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n" +inmapRight,"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n" +inmapRightAsync,"\n// Basic usage:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n\n// Process sequentially:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n" +inspectSinkStream,"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n" +inspectStream,"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n" +instanceOf,"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n" +INT8_MAX,"INT8_MAX\n" +INT8_MIN,"INT8_MIN\n" +INT8_NUM_BYTES,"INT8_NUM_BYTES\n" +Int8Array,"var arr = new Int8Array()\n" +INT16_MAX,"INT16_MAX\n" +INT16_MIN,"INT16_MIN\n" +INT16_NUM_BYTES,"INT16_NUM_BYTES\n" +Int16Array,"var arr = new Int16Array()\n" +INT32_MAX,"INT32_MAX\n" +INT32_MIN,"INT32_MIN\n" +INT32_NUM_BYTES,"INT32_NUM_BYTES\n" +Int32Array,"var arr = new Int32Array()\n" +IS_BIG_ENDIAN,"IS_BIG_ENDIAN\n" +IS_BROWSER,"IS_BROWSER\n" +IS_DARWIN,"IS_DARWIN\n" +IS_ELECTRON,"IS_ELECTRON\n" +IS_ELECTRON_MAIN,"IS_ELECTRON_MAIN\n" +IS_ELECTRON_RENDERER,"IS_ELECTRON_RENDERER\n" +IS_LITTLE_ENDIAN,"IS_LITTLE_ENDIAN\n" +IS_NODE,"IS_NODE\n" +IS_WEB_WORKER,"IS_WEB_WORKER\n" +IS_WINDOWS,"IS_WINDOWS\n" +isAbsolutePath,"\n// Windows environment:\nvar bool = isAbsolutePath( 'C:\\foo\\bar\\baz' )\n\n// POSIX environment:\nbool = isAbsolutePath( '/foo/bar/baz' )\n" +isAccessorProperty,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n" +isAccessorPropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n" +isAlphagram,"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n" +isAlphaNumeric,"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n" +isAnagram,"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n" +isArguments,"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n" +isArray,"var bool = isArray( [] )\nbool = isArray( {} )\n" +isArrayArray,"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n" +isArrayBuffer,"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n" +isArrayLength,"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n" +isArrayLike,"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n" +isArrayLikeObject,"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n" +isASCII,"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n" +isBetween,"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n" +isBetweenArray,"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n" +isBinaryString,"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n" +isBoolean,"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n" +isBooleanArray,"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n" +isBoxedPrimitive,"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n" +isBuffer,"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n" +isCapitalized,"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n" +isCentrosymmetricMatrix,"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 2, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n" +isCircular,"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n" +isCircularArray,"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n" +isCircularPlainObject,"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n" +isCollection,"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n" +isComplex,"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n" +isComplex64,"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n" +isComplex64Array,"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n" +isComplex128,"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n" +isComplex128Array,"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n" +isComplexLike,"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n" +isComplexTypedArray,"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n" +isConfigurableProperty,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n" +isConfigurablePropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n" +isDataProperty,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n" +isDataPropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n" +isDateObject,"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n" +isDigitString,"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n" +isEmailAddress,"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n" +isEmptyArray,"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n" +isEmptyObject,"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n" +isEmptyString,"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n" +isEnumerableProperty,"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n" +isEnumerablePropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n" +isError,"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n" +isEvalError,"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n" +isEven,"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n" +isFalsy,"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n" +isFalsyArray,"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n" +isFinite,"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n" +isFiniteArray,"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n" +isFloat32Array,"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n" +isFloat64Array,"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n" +isFunction,"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n" +isFunctionArray,"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n" +isGeneratorObject,"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n};\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n" +isGeneratorObjectLike,"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n};\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n" +isHexString,"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n" +isInfinite,"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n" +isInheritedProperty,"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n" +isInt8Array,"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n" +isInt16Array,"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n" +isInt32Array,"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n" +isInteger,"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n" +isIntegerArray,"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n" +isIterableLike,"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n" +isIteratorLike,"var obj = {\n 'next': function noop() {}\n};\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n" +isJSON,"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n" +isLeapYear,"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n" +isLowercase,"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n" +isMatrixLike,"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n" +isMethod,"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n" +isMethodIn,"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n" +isNamedTypedTupleLike,"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n" +isnan,"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n" +isNaNArray,"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n" +isNativeFunction,"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n" +isndarrayLike,"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n" +isNegativeInteger,"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n" +isNegativeIntegerArray,"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n" +isNegativeNumber,"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n" +isNegativeNumberArray,"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n" +isNegativeZero,"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n" +isNodeBuiltin,"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n" +isNodeDuplexStreamLike,"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n" +isNodeReadableStreamLike,"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n" +isNodeREPL,"var bool = isNodeREPL()\n" +isNodeStreamLike,"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n" +isNodeTransformStreamLike,"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n" +isNodeWritableStreamLike,"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n" +isNonConfigurableProperty,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n" +isNonConfigurablePropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n" +isNonEnumerableProperty,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n" +isNonEnumerablePropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n" +isNonNegativeInteger,"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n" +isNonNegativeIntegerArray,"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n" +isNonNegativeNumber,"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n" +isNonNegativeNumberArray,"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n" +isNonPositiveInteger,"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n" +isNonPositiveIntegerArray,"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n" +isNonPositiveNumber,"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n" +isNonPositiveNumberArray,"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n" +isNonSymmetricMatrix,"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n" +isNull,"var bool = isNull( null )\nbool = isNull( true )\n" +isNullArray,"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n" +isNumber,"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n" +isNumberArray,"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n" +isNumericArray,"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n" +isObject,"var bool = isObject( {} )\nbool = isObject( true )\n" +isObjectArray,"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n" +isObjectLike,"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n" +isOdd,"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n" +isoWeeksInYear,"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n" +isPersymmetricMatrix,"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 1, 2, 3, 1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n" +isPlainObject,"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n" +isPlainObjectArray,"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n" +isPositiveInteger,"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n" +isPositiveIntegerArray,"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n" +isPositiveNumber,"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n" +isPositiveNumberArray,"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n" +isPositiveZero,"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n" +isPrimitive,"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n" +isPrimitiveArray,"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n" +isPRNGLike,"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n" +isProbability,"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n" +isProbabilityArray,"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n" +isPrototypeOf,"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n" +isRangeError,"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n" +isReadableProperty,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n" +isReadablePropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n" +isReadOnlyProperty,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n" +isReadOnlyPropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n" +isReadWriteProperty,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n" +isReadWritePropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n" +isReferenceError,"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n" +isRegExp,"var bool = isRegExp( /\.+/ )\nbool = isRegExp( {} )\n" +isRegExpString,"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n" +isRelativePath,"\n// Windows environments:\nvar bool = isRelativePath( 'foo\\bar\\baz' )\n\n// POSIX environments:\nbool = isRelativePath( './foo/bar/baz' )\n" +isSafeInteger,"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n" +isSafeIntegerArray,"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n" +isSameValue,"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n" +isSameValueZero,"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n" +isSharedArrayBuffer,"\n// Assuming an environment supports SharedArrayBuffer...\nvar bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n" +isSkewCentrosymmetricMatrix,"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 2, 1, -1, -2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n" +isSkewPersymmetricMatrix,"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 1, 0, 0, -1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n" +isSkewSymmetricMatrix,"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 0, -1, 1, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n" +isSquareMatrix,"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 0, 0, 0, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n" +isStrictEqual,"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n" +isString,"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n" +isStringArray,"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n" +isSymbol,"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n" +isSymbolArray,"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n" +isSymmetricMatrix,"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 0, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n" +isSyntaxError,"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n" +isTruthy,"bool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n" +isTruthyArray,"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n" +isTypedArray,"var bool = isTypedArray( new Int8Array( 10 ) )\n" +isTypedArrayLength,"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n" +isTypedArrayLike,"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n 'length': 10,\n 'byteOffset': 0,\n 'byteLength': 10,\n 'BYTES_PER_ELEMENT': 4\n})\n" +isTypeError,"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n" +isUint8Array,"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n" +isUint8ClampedArray,"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n" +isUint16Array,"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n" +isUint32Array,"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n" +isUNCPath,"var bool = isUNCPath( '\\\\server\\share\\foo\\bar\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n" +isUndefined,"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n" +isUndefinedOrNull,"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n" +isUnityProbabilityArray,"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n" +isUppercase,"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n" +isURI,"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n\n// No scheme:\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\n\n// Illegal characters:\nbool = isURI( 'http://' )\n\n// Invalid path:\nbool = isURI( 'http:////foo.html' )\n\n// Incomplete hex escapes:\nbool = isURI( 'http://example.w3.org/%a' )\n" +isURIError,"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n" +isVectorLike,"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n" +isWhitespace,"var bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n" +isWritableProperty,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n" +isWritablePropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n" +isWriteOnlyProperty,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n" +isWriteOnlyPropertyIn,"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n" +iterAdd,"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" +iterAdvance,"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n" +iterAny,"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n" +iterAnyBy,"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n" +iterator2array,"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n" +iterator2arrayview,"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n" +iterator2arrayviewRight,"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n" +iteratorStream,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +IteratorSymbol,"var s = IteratorSymbol\n" +iterawgn,"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n" +iterawln,"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n" +iterawun,"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n" +iterBartlettHannPulse,"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n" +iterBartlettPulse,"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n" +iterConcat,"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" +iterConstant,"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n" +iterCosineWave,"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n" +iterCounter,"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n" +itercugmean,"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n" +itercuhmean,"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n" +itercumax,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itercumaxabs,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itercumean,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itercumeanabs,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itercumeanabs2,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itercumidrange,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n" +itercumin,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itercuminabs,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itercuprod,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n" +itercurange,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n" +itercusum,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n" +itercusumabs,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n" +itercusumabs2,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n" +iterDedupe,"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n" +iterDedupeBy,"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n" +iterDiracComb,"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n" +iterDivide,"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" +iterEmpty,"var it = iterEmpty();\nvar bool = it.next().done\n" +iterEvery,"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n" +iterEveryBy,"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n" +iterFibonacci,"var it = iterFibonacci();\nvar v = it.next().value\nv = it.next().value\n" +iterFill,"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n" +iterFilter,"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n" +iterFilterMap,"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n" +iterFirst,"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n" +iterFlatTopPulse,"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n" +iterFlow,"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n" +iterForEach,"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n" +iterHannPulse,"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n" +iterHead,"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n" +iterIntersection,"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" +iterIntersectionByHash,"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" +iterLanczosPulse,"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n" +iterLast,"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n" +iterLength,"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n" +iterMap,"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n" +iterMapN,"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" +itermax,"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n" +itermaxabs,"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n" +itermean,"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n" +itermeanabs,"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n" +itermeanabs2,"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n" +itermidrange,"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n" +itermin,"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n" +iterminabs,"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n" +itermmax,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itermmaxabs,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itermmean,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itermmeanabs,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itermmeanabs2,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itermmidrange,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n" +itermmin,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itermminabs,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +iterMod,"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" +itermprod,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n" +itermrange,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n" +itermsum,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n" +itermsumabs,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n" +itermsumabs2,"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n" +iterMultiply,"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" +iterNone,"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n" +iterNoneBy,"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n" +iterNonFibonacci,"var it = iterNonFibonacci();\nvar v = it.next().value\nv = it.next().value\n" +iterNth,"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n" +iterPeriodicSinc,"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n" +iterPipeline,"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n" +iterPop,"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n" +iterprod,"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n" +iterPulse,"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n" +iterPush,"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n" +iterrange,"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n" +iterReject,"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n" +iterReplicate,"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n" +iterReplicateBy,"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n" +iterSawtoothWave,"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n" +iterShift,"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n" +iterSineWave,"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n" +iterSlice,"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n" +iterSome,"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n" +iterSomeBy,"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n" +iterSquareWave,"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n" +iterstdev,"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n" +iterSubtract,"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" +itersum,"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n" +itersumabs,"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n" +itersumabs2,"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n" +iterThunk,"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n" +iterTriangleWave,"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n" +iterUnion,"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n" +iterUnique,"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n" +iterUniqueBy,"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n" +iterUniqueByHash,"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n" +iterUnshift,"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n" +itervariance,"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n" +joinStream,"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n" +keyBy,"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n" +keyByRight,"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n" +keysIn,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n" +kruskalTest,"\n// Data from Hollander & Wolfe (1973), p. 116:\nvar x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n];\nout = kruskalTest( arr, { 'groups': groups })\n" +kstest,"\n// Verify that data is drawn from a normal distribution:\nvar rnorm = base.random.normal.factory({ 'seed': 4839 });\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n// Test against N(0,1)\nvar out = kstest( x, 'normal', 0.0, 1.0 )\n\n// Test against N(3,1)\nout = kstest( x, 'normal', 3.0, 1.0 )\n\n// Verify that data is drawn from a uniform distribution:\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 })\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\n\n// Print output:\nout.print()\n\n// Set custom significance level:\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 })\n\n// Carry out one-sided hypothesis tests:\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 });\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' })\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' })\n\n// Set `sorted` option to true when data is in increasing order:\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true })\n" +LinkedList,"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n" +linspace,"var arr = linspace( 0, 100, 6 )\n" +LIU_NEGATIVE_OPINION_WORDS_EN,"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n" +LIU_POSITIVE_OPINION_WORDS_EN,"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n" +LN_HALF,"LN_HALF\n" +LN_PI,"LN_PI\n" +LN_SQRT_TWO_PI,"LN_SQRT_TWO_PI\n" +LN_TWO_PI,"LN_TWO_PI\n" +LN2,"LN2\n" +LN10,"LN10\n" +LOG2E,"LOG2E\n" +LOG10E,"LOG10E\n" +logspace,"var arr = logspace( 0, 2, 6 )\n" +lowercase,"var out = lowercase( 'bEEp' )\n" +lowercaseKeys,"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n" +lowess,"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n}\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n" +lpad,"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n" +ltrim,"var out = ltrim( ' \r\n\t Beep \t\t\n ' )\n" +MALE_FIRST_NAMES_EN,"var list = MALE_FIRST_NAMES_EN()\n" +mapFun,"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n" +mapFunAsync,"\n// Basic usage:\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n};\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n};\nmapFunAsync( fcn, 10, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n};\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n};\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\n\n// Sequential invocation:\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n};\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n};\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n" +mapKeys,"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n" +mapKeysAsync,"\n// Basic usage:\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\n\n// Limit number of concurrent invocations:\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n\n// Process sequentially:\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n" +mapValues,"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n" +mapValuesAsync,"\n// Basic usage:\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\n\n// Limit number of concurrent invocations:\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n\n// Process sequentially:\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n" +MAX_ARRAY_LENGTH,"MAX_ARRAY_LENGTH\n" +MAX_TYPED_ARRAY_LENGTH,"MAX_TYPED_ARRAY_LENGTH\n" +memoize,"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n};\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n" +merge,"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n" +MILLISECONDS_IN_DAY,"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n" +MILLISECONDS_IN_HOUR,"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n" +MILLISECONDS_IN_MINUTE,"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n" +MILLISECONDS_IN_SECOND,"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n" +MILLISECONDS_IN_WEEK,"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n" +MINARD_NAPOLEONS_MARCH,"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar river = data.river\nvar t = data.temperature\n" +MINUTES_IN_DAY,"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n" +MINUTES_IN_HOUR,"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n" +MINUTES_IN_WEEK,"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n" +minutesInMonth,"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n" +minutesInYear,"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n" +MOBY_DICK,"var data = MOBY_DICK()\n" +MONTH_NAMES_EN,"var list = MONTH_NAMES_EN()\n" +MONTHS_IN_YEAR,"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n" +moveProperty,"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n" +namedtypedtuple,"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n" +nativeClass,"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n" +ndarray,"var ctor = ndarray( 'generic', 2 )\n\n// To create a new instance...\nvar b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nvar v = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n" +ndarrayCastingModes,"var out = ndarrayCastingModes()\n" +ndarrayDataTypes,"var out = ndarrayDataTypes()\n" +ndarrayIndexModes,"var out = ndarrayIndexModes()\n" +ndarrayMemoized,"var ctor = ndarrayMemoized( 'generic', 2 )\nvar f = ndarrayMemoized( 'generic', 2 )\nvar bool = ( f === ctor )\n\n// To create a new instance...\nvar b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nvar v = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n" +ndarrayMinDataType,"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n" +ndarrayNextDataType,"var out = ndarrayNextDataType( 'float32' )\n" +ndarrayOrders,"var out = ndarrayOrders()\n" +ndarrayPromotionRules,"var out = ndarrayPromotionRules( 'float32', 'int32' )\n" +ndarraySafeCasts,"var out = ndarraySafeCasts( 'float32' )\n" +ndarraySameKindCasts,"var out = ndarraySameKindCasts( 'float32' )\n" +NIGHTINGALES_ROSE,"var data = NIGHTINGALES_ROSE()\n" +NINF,"NINF\n" +NODE_VERSION,"NODE_VERSION\n" +none,"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n" +noneBy,"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n" +noneByAsync,"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n" +noneByRight,"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n" +noneByRightAsync,"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n" +nonEnumerableProperties,"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n" +nonEnumerablePropertiesIn,"var props = nonEnumerablePropertiesIn( [] )\n" +nonEnumerablePropertyNames,"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n" +nonEnumerablePropertyNamesIn,"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n" +nonEnumerablePropertySymbols,"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n" +nonEnumerablePropertySymbolsIn,"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbolsIn( obj )\n" +noop,"noop();\n" +now,"var ts = now()\n" +NUM_CPUS,"NUM_CPUS\n" +Number,"var v = new Number( 5 )\n" +objectEntries,"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n" +objectEntriesIn,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n" +objectFromEntries,"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n" +objectInverse,"\n// Basic usage:\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\n\n// Duplicate values:\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\n\n// Override duplicate values:\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n" +objectInverseBy,"\n// Basic usage:\nfunction transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\n\n// Duplicate values:\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\n\n// Override duplicate values:\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n" +objectKeys,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n" +objectValues,"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n" +objectValuesIn,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n" +omit,"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n" +omitBy,"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n" +openURL,"var out = openURL( 'https://google.com' );\n" +PACE_BOSTON_HOUSE_PRICES,"var data = PACE_BOSTON_HOUSE_PRICES()\n" +pad,"\n// Standard usage:\nvar out = pad( 'a', 5 )\n\n// Left pad:\nout = pad( 'a', 10, { 'lpad': 'b' })\n\n// Right pad:\nout = pad( 'a', 12, { 'rpad': 'b' })\n\n// Center an input string:\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\n\n// Left center:\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\n\n// Right center:\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\n\n// Output string always length `len`:\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\n\n// Pad right, trim right:\nout = pad( 'beep', 2 )\n\n// Pad left, trim left:\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\n\n// Pad both, trim both:\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\n\n// Pad both, trim both starting from left:\nout = pad( 'abcdef', 3, opts )\n\n// Pad both, trim both starting from right:\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n" +papply,"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n" +papplyRight,"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n" +parallel,"function done( error ) { if ( error ) { throw error; } };\nvar files = [ './a.js', './b.js' ];\nparallel( files, done );\n\n// Specify the number of workers:\nvar opts = { 'workers': 8 };\nparallel( files, opts, done );\n" +parseJSON,"var obj = parseJSON( '{\"beep\":\"boop\"}' )\n\n// Provide a reviver:\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n};\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n" +PATH_DELIMITER,"PATH_DELIMITER\n\n// POSIX environment:\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\n\n// Windows environment:\npath = 'C:\\Windows\\system32;C:\\Windows';\nparts = path.split( PATH_DELIMITER )\n" +PATH_DELIMITER_POSIX,"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n" +PATH_DELIMITER_WIN32,"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\Windows\\system32;C:\\Windows;C:\\Program Files\\node\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n" +PATH_SEP,"PATH_SEP\n\n// Windows environment:\nvar parts = 'foo\\bar\\baz'.split( PATH_SEP )\n\n// POSIX environment:\nparts = 'foo/bar/baz'.split( PATH_SEP )\n" +PATH_SEP_POSIX,"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n" +PATH_SEP_WIN32,"PATH_SEP_WIN32\nvar parts = 'foo\\bar\\baz'.split( PATH_SEP_WIN32 )\n" +pcorrtest,"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\n x[ i ] = base.random.normal( 0.0, 1.0 );\n y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n base.sqrt( 1.0 - (rho*rho) ) );\n}\nvar out = pcorrtest( x, y )\n\n// Print output:\nvar table = out.print()\n" +percentEncode,"var out = percentEncode( '☃' )\n" +PHI,"PHI\n" +PI,"PI\n" +PI_SQUARED,"PI_SQUARED\n" +pick,"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n" +pickBy,"function predicate( key, value ) {\n return ( value > 1 );\n};\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n" +PINF,"PINF\n" +pkg2alias,"var v = pkg2alias( '@stdlib/math/base/special/sin' )\n" +pkg2related,"var v = pkg2related( '@stdlib/math/base/special/sin' )\n" +PLATFORM,"PLATFORM\n" +plot,"var plot = plot()\n\n// Provide plot data at instantiation:\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n" +Plot,"var plot = Plot()\n\n// Provide plot data at instantiation:\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n" +pluck,"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n" +pop,"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\n\n// Array-like object:\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n" +prepend,"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\n\n// Array-like object:\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n" +properties,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n" +propertiesIn,"var props = propertiesIn( [] )\n" +propertyDescriptor,"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n" +propertyDescriptorIn,"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n" +propertyDescriptors,"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n" +propertyDescriptorsIn,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n" +propertyNames,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n" +propertyNamesIn,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n" +propertySymbols,"var s = propertySymbols( {} )\n" +propertySymbolsIn,"var s = propertySymbolsIn( [] )\n" +Proxy,"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n" +push,"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\n\n// Array-like object:\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n" +quarterOfYear,"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\n\n// Other ways to supply month:\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n" +random.iterators.arcsine,"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.bernoulli,"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.beta,"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.betaprime,"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.binomial,"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.boxMuller,"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.cauchy,"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.chi,"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.chisquare,"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.cosine,"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.discreteUniform,"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.erlang,"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.exponential,"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.f,"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.frechet,"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.gamma,"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.geometric,"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.gumbel,"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.hypergeometric,"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.improvedZiggurat,"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.invgamma,"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.kumaraswamy,"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.laplace,"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.levy,"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.logistic,"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.lognormal,"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.minstd,"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.minstdShuffle,"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.mt19937,"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.negativeBinomial,"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.normal,"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.pareto1,"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.poisson,"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.randi,"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.randn,"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.randu,"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.rayleigh,"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.t,"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.triangular,"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.uniform,"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.iterators.weibull,"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n" +random.streams.arcsine,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.bernoulli,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.beta,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.betaprime,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.binomial,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.boxMuller,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.cauchy,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.chi,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.chisquare,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.cosine,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.discreteUniform,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.erlang,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.exponential,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.f,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.gamma,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.geometric,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.gumbel,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.improvedZiggurat,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.invgamma,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.kumaraswamy,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.laplace,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.levy,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.logistic,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.lognormal,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.minstd,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.minstdShuffle,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.mt19937,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.negativeBinomial,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.normal,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.pareto1,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.poisson,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.randi,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.randn,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.randu,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.rayleigh,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.t,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.uniform,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +random.streams.weibull,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +ranks,"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\n\n// Ties are averaged:\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\n\n// Missing values are placed last:\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n" +RE_BASENAME,"var base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]\n" +RE_BASENAME_POSIX,"var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n" +RE_BASENAME_WINDOWS,"var base = RE_BASENAME_WINDOWS.exec( '\\foo\\bar\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\bar\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n" +RE_COLOR_HEXADECIMAL,"var bool = RE_COLOR_HEXADECIMAL.test( 'ffffff' )\nbool = RE_COLOR_HEXADECIMAL.test( '000' )\nbool = RE_COLOR_HEXADECIMAL.test( 'beep' )\n" +RE_DECIMAL_NUMBER,"var bool = RE_DECIMAL_NUMBER.test( '1.234' )\nbool = RE_DECIMAL_NUMBER.test( '-1.234' )\nbool = RE_DECIMAL_NUMBER.test( '0.0' )\nbool = RE_DECIMAL_NUMBER.test( '.0' )\nbool = RE_DECIMAL_NUMBER.test( '0' )\nbool = RE_DECIMAL_NUMBER.test( 'beep' )\n\n// Create a RegExp to capture all decimal numbers:\nvar re = new RegExp( RE_DECIMAL_NUMBER.source, 'g' );\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n" +RE_DIRNAME,"var dir = RE_DIRNAME.exec( '/foo/bar/index.js' )[ 1 ]\n" +RE_DIRNAME_POSIX,"var dir = RE_DIRNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( 'index.js' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( '.' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( './' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( '' )[ 1 ]\n" +RE_DIRNAME_WINDOWS,"var dir = RE_DIRNAME_WINDOWS.exec( 'foo\\bar\\index.js' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( '\\foo\\bar\\file' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( 'index.js' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( '' )[ 1 ]\n" +RE_EOL,"var bool = RE_EOL.test( '\n' )\nbool = RE_EOL.test( '\r\n' )\nbool = RE_EOL.test( '\\r\\n' )\n" +RE_EXTENDED_LENGTH_PATH,"var path = '\\\\?\\C:\\foo\\bar';\nvar bool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = '\\\\?\\UNC\\server\\share';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = 'C:\\foo\\bar';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = '/c/foo/bar';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = '/foo/bar';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\n" +RE_EXTNAME,"var dir = RE_EXTNAME.exec( '/foo/bar/index.js' )[ 1 ]\n" +RE_EXTNAME_POSIX,"var ext = RE_EXTNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( 'index.js' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( '.' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( './' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( '' )[ 1 ]\n" +RE_EXTNAME_WINDOWS,"var ext = RE_EXTNAME_WINDOWS.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'C:\\foo\\bar\\.gitignore' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'foo\\file.pdf' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( '\\foo\\bar\\file' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'beep\\boop.' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'index.js' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( '' )[ 1 ]\n" +RE_FILENAME,"var f = '/foo/bar/index.js';\nvar parts = RE_FILENAME.exec( f ).slice()\n" +RE_FILENAME_POSIX,"var parts = RE_FILENAME_POSIX.exec( '/foo/bar/index.js' ).slice()\nparts = RE_FILENAME_POSIX.exec( './foo/bar/.gitignore' ).slice()\nparts = RE_FILENAME_POSIX.exec( 'foo/file.pdf' ).slice()\nparts = RE_FILENAME_POSIX.exec( '/foo/bar/file' ).slice()\nparts = RE_FILENAME_POSIX.exec( 'index.js' ).slice()\nparts = RE_FILENAME_POSIX.exec( '.' ).slice()\nparts = RE_FILENAME_POSIX.exec( './' ).slice()\nparts = RE_FILENAME_POSIX.exec( '' ).slice()\n" +RE_FILENAME_WINDOWS,"var parts = RE_FILENAME_WINDOWS.exec( 'C:\\foo\\bar\\index.js' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '\\foo\\bar\\.gitignore' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( 'foo\\file.pdf' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '\\foo\\bar\\file' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( 'index.js' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '.' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( './' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '' ).slice()\n" +RE_FUNCTION_NAME,"function beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n" +RE_NATIVE_FUNCTION,"var bool = RE_NATIVE_FUNCTION.test( Date.toString() )\nbool = RE_NATIVE_FUNCTION.test( (function noop() {}).toString() )\n" +RE_REGEXP,"var bool = RE_REGEXP.test( '/^beep$/' )\nbool = RE_REGEXP.test( '/boop' )\n\n// Escape regular expression strings:\nbool = RE_REGEXP.test( '/^\/([^\/]+)\/(.*)$/' )\nbool = RE_REGEXP.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n" +RE_UNC_PATH,"var path = '\\\\server\\share\\foo\\bar\\baz:a:b';\nvar bool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\foo\\bar\\baz::b';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\foo\\bar\\baz:a';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\foo\\bar\\baz';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\foo\\bar';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\foo';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\\\share';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\share';\nbool = RE_UNC_PATH.test( path )\npath = 'beep boop \\\\server\\share';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server';\nbool = RE_UNC_PATH.test( path )\npath = '\\';\nbool = RE_UNC_PATH.test( path )\npath = '';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\foo\\bar\\baz:';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\foo\\bar\\baz:a:';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\foo\\bar\\baz::';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\foo\\bar\\baz:a:b:c';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\server\\share\\foo\\bar\\';\nbool = RE_UNC_PATH.test( path )\npath = '//server/share';\nbool = RE_UNC_PATH.test( path )\npath = '/foo/bar';\nbool = RE_UNC_PATH.test( path )\npath = 'foo/bar';\nbool = RE_UNC_PATH.test( path )\npath = './foo/bar';\nbool = RE_UNC_PATH.test( path )\npath = '/foo/../bar';\nbool = RE_UNC_PATH.test( path )\n" +RE_UTF16_SURROGATE_PAIR,"var bool = RE_UTF16_SURROGATE_PAIR.test( 'abc\uD800\uDC00def' )\nbool = RE_UTF16_SURROGATE_PAIR.test( 'abcdef' )\n" +RE_UTF16_UNPAIRED_SURROGATE,"var bool = RE_UTF16_UNPAIRED_SURROGATE.test( 'abc' )\nbool = RE_UTF16_UNPAIRED_SURROGATE.test( '\uD800' )\n" +RE_WHITESPACE,"var bool = RE_WHITESPACE.test( '\n' )\nbool = RE_WHITESPACE.test( ' ' )\nbool = RE_WHITESPACE.test( 'a' )\n" +readDir,"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadDir( './beep/boop', onRead );\n" +readFile,"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadFile( './beep/boop.js', onRead );\n" +readFileList,"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n" +readJSON,"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadJSON( './beep/boop.json', onRead );\n" +readWASM,"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadWASM( './beep/boop.wasm', onRead );\n" +real,"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n" +realmax,"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n" +realmin,"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n" +reduce,"function sum( acc, v ) { return acc + v; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = reduce( arr, 0, sum )\n" +reduceAsync,"\n// Basic usage:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n\n// Process concurrently:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n" +reduceRight,"function sum( acc, v ) {\n console.log( '%s: %d', acc, v );\n return acc + v;\n};\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = reduceRight( arr, 0, sum );\nout\n" +reduceRightAsync,"\n// Basic usage:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n\n// Process concurrently:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n" +reFromString,"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n" +reim,"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n" +removeFirst,"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\n" +removeLast,"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\n" +removePunctuation,"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\'\"';\nout = removePunctuation( str )\n" +removeUTF8BOM,"var out = removeUTF8BOM( '\ufeffbeep' )\n" +removeWords,"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n\n// Case-insensitive:\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n" +rename,"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n};\nrename( './beep/boop.txt', './beep/foo.txt', done );\n" +reorderArguments,"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n" +repeat,"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n" +replace,"\n// Standard usage:\nvar out = replace( 'beep', 'e', 'o' )\n\n// Replacer function:\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\s]+)/gi, replacer )\n\n// Replace only first match:\nout = replace( 'beep', /e/, 'o' )\n" +rescape,"var str = rescape( '[A-Z]*' )\n" +resolveParentPath,"function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n};\nresolveParentPath( 'package.json', onPath );\n" +reverseArguments,"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n" +reverseString,"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n" +reviveBasePRNG,"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n" +reviveBuffer,"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n" +reviveComplex,"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n" +reviveComplex64,"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n" +reviveComplex128,"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n" +reviveError,"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n" +reviveTypedArray,"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n" +rpad,"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n" +rtrim,"var out = rtrim( ' \t\t\n Beep \r\n\t ' )\n" +safeintmax,"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n" +safeintmin,"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n" +sample,"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\n\n// Set sample size:\nout = sample( [ 3, 6, 9 ], { 'size': 10 })\nout = sample( [ 0, 1 ], { 'size': 20 })\n\n// Draw without replacement:\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 })\nout = sample( [ 0, 1 ], { 'replace': false })\n\n// Assigning non-uniform element probabilities:\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs })\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false })\n" +SAVOY_STOPWORDS_FIN,"var list = SAVOY_STOPWORDS_FIN()\n" +SAVOY_STOPWORDS_FR,"var list = SAVOY_STOPWORDS_FR()\n" +SAVOY_STOPWORDS_GER,"var list = SAVOY_STOPWORDS_GER()\n" +SAVOY_STOPWORDS_IT,"var list = SAVOY_STOPWORDS_IT()\n" +SAVOY_STOPWORDS_POR,"var list = SAVOY_STOPWORDS_POR()\n" +SAVOY_STOPWORDS_SP,"var list = SAVOY_STOPWORDS_SP()\n" +SAVOY_STOPWORDS_SWE,"var list = SAVOY_STOPWORDS_SWE()\n" +SECONDS_IN_DAY,"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n" +SECONDS_IN_HOUR,"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n" +SECONDS_IN_MINUTE,"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n" +SECONDS_IN_WEEK,"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n" +secondsInMonth,"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n" +secondsInYear,"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n" +setConfigurableReadOnly,"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n" +setConfigurableReadOnlyAccessor,"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n" +setConfigurableReadWriteAccessor,"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n" +setConfigurableWriteOnlyAccessor,"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n" +setMemoizedReadOnly,"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n" +setNonEnumerableProperty,"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n" +setNonEnumerableReadOnly,"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n" +setNonEnumerableReadOnlyAccessor,"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n" +setNonEnumerableReadWriteAccessor,"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n" +setNonEnumerableWriteOnlyAccessor,"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n" +setReadOnly,"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n" +setReadOnlyAccessor,"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n" +setReadWriteAccessor,"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n" +setWriteOnlyAccessor,"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n" +SharedArrayBuffer,"\n// Assuming an environment supports SharedArrayBuffers...\nvar buf = new SharedArrayBuffer( 5 )\n" +shift,"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\n\n// Array-like object:\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n" +shuffle,"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' });\nvar bool = ( data === out )\n" +sizeOf,"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n" +some,"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n" +someBy,"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n" +someByAsync,"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n" +someByRight,"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n" +someByRightAsync,"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n" +SOTU,"var out = SOTU()\n\n// Retrieve addresses by one or more Presidents...\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\n\n// Retrieve addresses by one or more political parties...\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\n\n// Retrieve addresses from one or more years...\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\n\n// Retrieve addresses from a range of consecutive years...\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n" +SPACHE_REVISED,"var list = SPACHE_REVISED()\n" +SPAM_ASSASSIN,"var data = SPAM_ASSASSIN()\n" +SparklineBase,"var sparkline = new SparklineBase()\n\n// Provide sparkline data at instantiation:\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n" +sparsearray2iterator,"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n" +sparsearray2iteratorRight,"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n" +splitStream,"var s = splitStream();\ns.write( 'a\nb\nc' );\ns.end();\n" +SQRT_EPS,"SQRT_EPS\n" +SQRT_HALF,"SQRT_HALF\n" +SQRT_HALF_PI,"SQRT_HALF_PI\n" +SQRT_PHI,"SQRT_PHI\n" +SQRT_PI,"SQRT_PI\n" +SQRT_THREE,"SQRT_THREE\n" +SQRT_TWO,"SQRT_TWO\n" +SQRT_TWO_PI,"SQRT_TWO_PI\n" +Stack,"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n" +startcase,"var out = startcase( 'beep boop' )\n" +startsWith,"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n" +STOPWORDS_EN,"var list = STOPWORDS_EN()\n" +stridedarray2iterator,"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n" +stridedArrayStream,"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n" +string2buffer,"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n" +sub2ind,"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n" +SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK,"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n" +SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK,"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n" +Symbol,"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n" +tabulate,"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n" +tabulateBy,"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n" +tabulateByAsync,"\n// Basic usage:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\n\n// Limit number of concurrent invocations:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n\n// Process sequentially:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n" +tic,"var t = tic()\n" +timeit,"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \'Something went wrong.\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n};\ntimeit( code, done )\n" +tmpdir,"var dir = tmpdir()\n" +toc,"var start = tic();\nvar delta = toc( start )\n" +tokenize,"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n" +transformStream,"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n" +trim,"var out = trim( ' \t\t\n Beep \r\n\t ' )\n" +trycatch,"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n};\nvar z = trycatch( x, -1.0 )\n" +trycatchAsync,"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n};\ntrycatchAsync( x, 'boop', done )\n" +tryFunction,"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n" +tryRequire,"var out = tryRequire( '_unknown_module_id_' )\n" +trythen,"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n};\nfunction y() {\n return -1.0;\n};\nvar z = trythen( x, y )\n" +trythenAsync,"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n};\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\ntrythenAsync( x, y, done )\n" +ttest,"\n// One-sample t-test:\nvar rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 });\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n}\nvar out = ttest( x )\n\n// Paired t-test:\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 });\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n}\nout = ttest( x, y )\n\n// Print formatted output:\nvar table = out.print()\n\n// Choose custom significance level:\narr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 });\ntable = out.print()\n\n// Test for a mean equal to five:\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 })\n\n// Perform one-sided tests:\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' });\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' });\ntable = out.print()\n" +ttest2,"\n// Student's sleep data:\nvar x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\n\n// Print table output:\nvar table = out.print()\n\n// Choose a different significance level than `0.05`:\nout = ttest2( x, y, { 'alpha': 0.1 });\ntable = out.print()\n\n// Perform one-sided tests:\nout = ttest2( x, y, { 'alternative': 'less' });\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' });\ntable = out.print()\n\n// Run tests with equal variances assumption:\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' });\ntable = out.print()\n\n// Test for a difference in means besides zero:\nvar rnorm = base.random.normal.factory({ 'seed': 372 });\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n}\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n}\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' })\n" +TWO_PI,"TWO_PI\n" +typedarray,"var arr = typedarray()\narr = typedarray( 'float32' )\n" +typedarray2json,"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n" +typedarrayComplexCtors,"var ctor = typedarrayComplexCtors( 'complex64' )\nctor = typedarrayComplexCtors( 'float32' )\n" +typedarrayComplexDataTypes,"var out = typedarrayComplexDataTypes()\n" +typedarrayCtors,"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n" +typedarrayDataTypes,"var out = typedarrayDataTypes()\n" +typedarraypool,"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\n" +typemax,"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n" +typemin,"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n" +typeOf,"\n// Built-ins:\nvar t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\n\n// Arguments object:\nfunction beep() { return arguments; };\nt = typeOf( beep() )\n\n// Node.js Buffer object:\nt = typeOf( new Buffer( 10 ) )\n\n// Custom constructor:\nfunction Person() { return this };\nt = typeOf( new Person() )\n\n// Anonymous constructor:\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n" +UINT8_MAX,"UINT8_MAX\n" +UINT8_NUM_BYTES,"UINT8_NUM_BYTES\n" +Uint8Array,"var arr = new Uint8Array()\n" +Uint8ClampedArray,"var arr = new Uint8ClampedArray()\n" +UINT16_MAX,"UINT16_MAX\n" +UINT16_NUM_BYTES,"UINT16_NUM_BYTES\n" +Uint16Array,"var arr = new Uint16Array()\n" +UINT32_MAX,"UINT32_MAX\n" +UINT32_NUM_BYTES,"UINT32_NUM_BYTES\n" +Uint32Array,"var arr = new Uint32Array()\n" +umask,"var mask = umask()\nmask = umask( { 'symbolic': true } )\n" +uncapitalize,"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n" +uncapitalizeKeys,"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n" +uncurry,"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n};\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\n\n// To enforce a fixed number of parameters, provide an `arity` argument:\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n};\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\n\n// To specify an execution context, provide a `thisArg` argument:\nfunction addX( x ) {\n this.x = x;\n return addY;\n};\nfunction addY( y ) {\n return this.x + y;\n};\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n" +uncurryRight,"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n};\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\n\n// To enforce a fixed number of parameters, provide an `arity` argument:\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n};\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\n\n// To specify an execution context, provide a `thisArg` argument:\nfunction addY( y ) {\n this.y = y;\n return addX;\n};\nfunction addX( x ) {\n return x + this.y;\n};\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n" +UNICODE_MAX,"UNICODE_MAX\n" +UNICODE_MAX_BMP,"UNICODE_MAX_BMP\n" +UnicodeColumnChartSparkline,"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n" +UnicodeLineChartSparkline,"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n" +UnicodeSparkline,"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n" +UnicodeTristateChartSparkline,"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n" +UnicodeUpDownChartSparkline,"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n" +UnicodeWinLossChartSparkline,"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n" +unlink,"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n};\nunlink( './beep/boop.txt', done );\n" +unshift,"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\n\n// Array-like object:\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n" +until,"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n" +untilAsync,"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nuntilAsync( predicate, fcn, done )\n" +untilEach,"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n" +untilEachRight,"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n" +unzip,"\n// Basic usage:\nvar arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\n\n// Provide indices:\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n" +uppercase,"var out = uppercase( 'bEEp' )\n" +uppercaseKeys,"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n" +US_STATES_ABBR,"var list = US_STATES_ABBR()\n" +US_STATES_CAPITALS,"var list = US_STATES_CAPITALS()\n" +US_STATES_CAPITALS_NAMES,"var out = US_STATES_CAPITALS_NAMES()\n" +US_STATES_NAMES,"var list = US_STATES_NAMES()\n" +US_STATES_NAMES_CAPITALS,"var out = US_STATES_NAMES_CAPITALS()\n" +utf16ToUTF8Array,"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n" +vartest,"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\n\n// Print table output:\nvar table = out.print()\n" +waterfall,"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n" +whileAsync,"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nwhileAsync( predicate, fcn, done )\n" +whileEach,"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n" +whileEachRight,"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n" +whilst,"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n" +writableProperties,"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n" +writablePropertiesIn,"var props = writablePropertiesIn( [] )\n" +writablePropertyNames,"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n" +writablePropertyNamesIn,"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n" +writablePropertySymbols,"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n" +writablePropertySymbolsIn,"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n" +writeFile,"function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n};\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n" +zip,"\n// Basic usage:\nvar out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n\n// Turn off truncation:\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n" +ztest,"\n// One-sample z-test:\nvar rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 });\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n}\nvar out = ztest( x, 2.0 )\n\n// Choose custom significance level and print output:\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 });\ntable = out.print()\n\n// Test for a mean equal to five:\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 })\n\n// Perform one-sided tests:\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' })\nout = ztest( arr, 1.0, { 'alternative': 'greater' })\n" +ztest2,"\n// Drawn from Normal(0,2):\nvar x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n// Drawn from Normal(1,2):\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\n\n// Print table output:\nvar table = out.print()\n\n// Choose a different significance level than `0.05`:\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 });\ntable = out.print()\n\n// Perform one-sided tests:\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' });\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' });\ntable = out.print()\n\n// Test for a difference in means besides zero:\nvar rnorm = base.random.normal.factory({ 'seed': 372 });\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n}\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n}\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 })\n" diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json new file mode 100644 index 000000000000..f3c117f722c1 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json @@ -0,0 +1 @@ +{"AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","aliases":"var o = aliases()\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n'control', 'treatA', 'treatB', 'treatC', 'control',\n'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","APERY":"APERY\n","append":"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\n\n// Array-like object:\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"\n// Create a 2x2 matrix:\nvar arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n\n// Get an element using subscripts:\nvar v = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","bartlettTest":"\n// Data from Hollander & Wolfe (1973), p. 116:\nvar x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n];\nout = bartlettTest( arr, { 'groups': groups })\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absInt32":"var v = base.absInt32( -1|0 )\nv = base.absInt32( 2|0 )\nv = base.absInt32( 0|0 )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( PI/2.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n","base.avercos":"var y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n","base.aversin":"var y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( 5.0, 3.0 )\n","base.cabs2":"var y = base.cabs2( 5.0, 3.0 )\n","base.cadd":"var y = base.cadd( 5.0, 3.0, -2.0, 1.0 )\n\n// Provide an output array:\nvar out = new Float32Array( 2 );\ny = base.cadd( out, 5.0, 3.0, -2.0, 1.0 )\nvar bool = ( y === out )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cceil":"var out = base.cceil( 5.5, 3.3 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cceil( out, 5.5, 3.3 )\nvar bool = ( v === out )\n","base.cceiln":"var out = base.cceiln( 5.555, -3.333, -2 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cceiln( out, 5.555, -3.333, -2 )\nvar bool = ( v === out )\n","base.ccis":"var y = base.ccis( 0.0, 0.0 )\nvar y = base.ccis( 1.0, 0.0 )\nvar out = new Float64Array( 2 );\nvar v = base.ccis( out, 1.0, 0.0 )\nvar bool = ( v === out )\n","base.cdiv":"var y = base.cdiv( -13.0, -1.0, -2.0, 1.0 )\nvar out = new Float64Array( 2 );\nvar v = base.cdiv( out, -13.0, -1.0, -2.0, 1.0 )\nvar bool = ( v === out )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"\n// Round to 4 decimal places:\nvar y = base.ceilb( 3.14159, -4, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.ceilb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two toward positive infinity:\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceiln":"\n// Round to 2 decimal places:\nvar y = base.ceiln( 3.14159, -2 )\n\n// If `n = 0`, standard round toward positive infinity behavior:\ny = base.ceiln( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5 )\ny = base.ceilsd( 3.14159, 1 )\ny = base.ceilsd( 12368.0, 2 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( 0.0, 0.0 )\ny = base.cexp( 0.0, 1.0 )\nvar out = new Float64Array( 2 );\nvar v = base.cexp( out, 0.0, 1.0 )\nvar bool = ( v === out )\n","base.cflipsign":"var out = base.cflipsign( -4.2, 5.5, -9 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cflipsign( out, -4.2, 5.5, 8 )\nvar bool = ( v === out )\n","base.cfloor":"var out = base.cfloor( 5.5, 3.3 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cfloor( out, 5.5, 3.3 )\nvar bool = ( v === out )\n","base.cfloorn":"var out = base.cfloorn( 5.555, -3.333, -2 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cfloorn( out, 5.555, -3.333, -2 )\nvar bool = ( v === out )\n","base.cinv":"var y = base.cinv( 2.0, 4.0 )\nvar out = new Float64Array( 2 );\nvar v = base.cinv( out, 2.0, 4.0 )\nvar bool = ( v === out )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.cmul":"var out = base.cmul( 5.0, 3.0, -2.0, 1.0 )\n\n// Provide an output array:\nvar out = new Float64Array( 2 );\nvar v = base.cmul( out, 5.0, 3.0, -2.0, 1.0 )\nvar bool = ( v === out )\n","base.cneg":"var out = base.cneg( -4.2, 5.5 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cneg( out, -4.2, 5.5 )\nvar bool = ( v === out )\n","base.continuedFraction":"\n// Continued fraction for (e-1)^(-1):\nfunction closure() {\n var i = 0;\n return function() {\n i += 1;\n return [ i, i ];\n };\n};\nvar gen = closure();\nvar out = base.continuedFraction( gen )\n\n// Using an ES6 generator:\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n};\ngen = generator();\nout = base.continuedFraction( gen )\n\n// Set options:\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( 5.0, 3.0 )\n","base.cpolar":"var out = base.cpolar( 5.0, 3.0 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cpolar( out, 5.0, 3.0 )\nvar bool = ( v === out )\n","base.cround":"var out = base.cround( 5.5, 3.3 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.cround( out, 5.5, 3.3 )\nvar bool = ( v === out )\n","base.croundn":"var out = base.croundn( 5.555, -3.336, -2 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.croundn( out, 5.555, -3.336, -2 )\nvar bool = ( v === out )\n","base.csignum":"var out = base.csignum( -4.2, 5.5 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.csignum( out, -4.2, 5.5 )\nvar bool = ( v === out )\n","base.csub":"var out = base.csub( 5.0, 3.0, -2.0, 1.0 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.csub( out, 5.0, 3.0, -2.0, 1.0 )\nvar bool = ( v === out )\n","base.dasum":"\n// Standard usage:\nvar x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\nvar sum = base.dasum( x.length, x, 1 )\n\n// Sum every other value:\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nsum = base.dasum( N, x, stride )\n\n// Use view offset; e.g., starting at 2nd element:\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nsum = base.dasum( N, x1, stride )\n","base.daxpy":"\n// Standard usage:\nvar x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.daxpy( x.length, alpha, x, 1, y, 1 )\n\n// Using `N` and `stride` parameters:\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.daxpy( N, alpha, x, 2, y, -1 )\n\n// Using view offsets:\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.daxpy( N, 5.0, x1, -2, y1, 1 )\ny0\n","base.dcopy":"\n// Standard usage:\nvar x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.dcopy( x.length, x, 1, y, 1 )\n\n// Advanced indexing:\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.dcopy( N, x, -2, y, 1 )\n\n// Using typed array views:\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.dcopy( N, x1, -2, y1, 1 )\ny0\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.dists.arcsine.Arcsine":"var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n","base.dists.arcsine.cdf":"var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\n\n// Invalid probability:\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\n\n// Invalid success probability:\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chi.cdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chi.logpdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chi.pdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chi.quantile( 0.5, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n\n// Degenerate distribution centered at `μ` when `s = 0.0`:\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n\n// Degenerate distribution centered at `μ` when `s = 0.0`:\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution at `s = 0.0`:\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.logpmf":"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\n\n// Non-integer shape parameter:\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n\n// Non-positive shape parameter:\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\n\n// Negative rate parameter:\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\n\n// Negative rate parameter:\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\n\n// Negative rate:\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\n\n// Negative rate:\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\n\n// Negative rate parameter:\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n","base.dists.exponential.skewness":"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n","base.dists.exponential.stdev":"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n","base.dists.exponential.variance":"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n","base.dists.f.cdf":"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\nvar y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n","base.dists.f.entropy":"var v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n","base.dists.f.F":"var f = base.dists.f.F( 6.0, 9.0 );\nf.d1\nf.d2\nf.entropy\nf.kurtosis\nf.mean\nf.mode\nf.skewness\nf.stdev\nf.variance\nf.cdf( 3.0 )\nf.pdf( 2.5 )\nf.quantile( 0.8 )\n","base.dists.f.kurtosis":"var v = base.dists.f.kurtosis( 3.0, 9.0 )\nv = base.dists.f.kurtosis( 4.0, 12.0 )\nv = base.dists.f.kurtosis( 8.0, 9.0 )\n","base.dists.f.mean":"var v = base.dists.f.mean( 3.0, 5.0 )\nv = base.dists.f.mean( 4.0, 12.0 )\nv = base.dists.f.mean( 8.0, 4.0 )\n","base.dists.f.mode":"var v = base.dists.f.mode( 3.0, 5.0 )\nv = base.dists.f.mode( 4.0, 12.0 )\nv = base.dists.f.mode( 8.0, 4.0 )\n","base.dists.f.pdf":"var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = base.dists.f.variance( 8.0, 5.0 )\n","base.dists.frechet.cdf":"var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.entropy":"var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\ny = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\ny = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\ny = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n","base.dists.frechet.Frechet":"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n","base.dists.frechet.kurtosis":"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.logpdf":"var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.mean":"var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n","base.dists.frechet.median":"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n","base.dists.frechet.mode":"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n","base.dists.frechet.pdf":"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0` when `α = 0.0`:\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0.0` when `α = 0.0`:\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.mean":"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n","base.dists.gamma.mgf":"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0.0` when `α = 0.0`:\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.quantile":"var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n\n// Non-positive shape parameter:\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0.0` when `α = 0.0`:\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\n\n// Invalid probability\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\n\n// Invalid probability\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\n\n// Invalid success probability:\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\n\n// Case: t >= -ln(1-p)\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\n\n// Invalid success probability:\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n\n// Case: `t >= 1/beta`\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n\n// Non-positive scale parameter:\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n\n// Negative scale parameter:\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n\n// Negative scale parameter:\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n\n// Non-positive shape parameter:\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.entropy":"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n","base.dists.laplace.kurtosis":"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n","base.dists.laplace.Laplace":"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n","base.dists.laplace.logcdf":"var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logpdf":"var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mean":"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n","base.dists.laplace.median":"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n","base.dists.laplace.mgf":"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mode":"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n","base.dists.laplace.pdf":"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.quantile":"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n","base.dists.laplace.skewness":"var y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n","base.dists.laplace.stdev":"var y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n","base.dists.laplace.variance":"var y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 )\n","base.dists.levy.cdf":"var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.cdf( 2, NaN, 1.0 )\ny = base.dists.levy.cdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.entropy":"var y = base.dists.levy.entropy( 0.0, 1.0 )\ny = base.dists.levy.entropy( 4.0, 2.0 )\ny = base.dists.levy.entropy( NaN, 1.0 )\ny = base.dists.levy.entropy( 0.0, NaN )\ny = base.dists.levy.entropy( 0.0, 0.0 )\n","base.dists.levy.Levy":"var levy = base.dists.levy.Levy( -2.0, 3.0 );\nlevy.mu\nlevy.c\nlevy.entropy\nlevy.mean\nlevy.median\nlevy.mode\nlevy.stdev\nlevy.variance\nlevy.cdf( 0.8 )\nlevy.logcdf( 0.8 )\nlevy.logpdf( 1.0 )\nlevy.pdf( 1.0 )\nlevy.quantile( 0.8 )\n","base.dists.levy.logcdf":"var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 2, NaN, 1.0 )\ny = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logpdf":"var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.mean":"var y = base.dists.levy.mean( 0.0, 1.0 )\ny = base.dists.levy.mean( 4.0, 3.0 )\ny = base.dists.levy.mean( NaN, 1.0 )\ny = base.dists.levy.mean( 0.0, NaN )\ny = base.dists.levy.mean( 0.0, 0.0 )\n","base.dists.levy.median":"var y = base.dists.levy.median( 0.0, 1.0 )\ny = base.dists.levy.median( 4.0, 3.0 )\ny = base.dists.levy.median( NaN, 1.0 )\ny = base.dists.levy.median( 0.0, NaN )\ny = base.dists.levy.median( 0.0, 0.0 )\n","base.dists.levy.mode":"var y = base.dists.levy.mode( 0.0, 1.0 )\ny = base.dists.levy.mode( 4.0, 3.0 )\ny = base.dists.levy.mode( NaN, 1.0 )\ny = base.dists.levy.mode( 0.0, NaN )\ny = base.dists.levy.mode( 0.0, 0.0 )\n","base.dists.levy.pdf":"var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.pdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.quantile":"var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.levy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.levy.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.levy.stdev":"var y = base.dists.levy.stdev( 0.0, 1.0 )\ny = base.dists.levy.stdev( 4.0, 3.0 )\ny = base.dists.levy.stdev( NaN, 1.0 )\ny = base.dists.levy.stdev( 0.0, NaN )\ny = base.dists.levy.stdev( 0.0, 0.0 )\n","base.dists.levy.variance":"var y = base.dists.levy.variance( 0.0, 1.0 )\ny = base.dists.levy.variance( 4.0, 3.0 )\ny = base.dists.levy.variance( NaN, 1.0 )\ny = base.dists.levy.variance( 0.0, NaN )\ny = base.dists.levy.variance( 0.0, 0.0 )\n","base.dists.logistic.cdf":"var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.cdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\ny = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n\n// Degenerate distribution centered at `μ` when `s = 0.0`:\ny = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n","base.dists.logistic.entropy":"var y = base.dists.logistic.entropy( 0.0, 1.0 )\ny = base.dists.logistic.entropy( 4.0, 2.0 )\ny = base.dists.logistic.entropy( NaN, 1.0 )\ny = base.dists.logistic.entropy( 0.0, NaN )\ny = base.dists.logistic.entropy( 0.0, 0.0 )\n","base.dists.logistic.kurtosis":"var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\ny = base.dists.logistic.kurtosis( 4.0, 2.0 )\ny = base.dists.logistic.kurtosis( NaN, 1.0 )\ny = base.dists.logistic.kurtosis( 0.0, NaN )\ny = base.dists.logistic.kurtosis( 0.0, 0.0 )\n","base.dists.logistic.logcdf":"var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.logcdf( 2, NaN, 1.0 )\ny = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n","base.dists.logistic.Logistic":"var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\nlogistic.mu\nlogistic.s\nlogistic.entropy\nlogistic.kurtosis\nlogistic.mean\nlogistic.median\nlogistic.mode\nlogistic.skewness\nlogistic.stdev\nlogistic.variance\nlogistic.cdf( 0.8 )\nlogistic.logcdf( 0.8 )\nlogistic.logpdf( 2.0 )\nlogistic.mgf( 0.2 )\nlogistic.pdf( 2.0 )\nlogistic.quantile( 0.9 )\n","base.dists.logistic.logpdf":"var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution at `s = 0.0`:\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.mean":"var y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n","base.dists.logistic.median":"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n","base.dists.logistic.mode":"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n","base.dists.logistic.pdf":"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.quantile":"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n","base.dists.logistic.skewness":"var y = base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\n\n// Negative mean parameter:\ny = base.dists.poisson.cdf( 2.0, -1.0 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\n\n// Negative mean parameter:\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\n\n// Negative mean parameter:\ny = base.dists.poisson.pmf( 2.0, -0.5 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\n\n// Negative mean parameter:\ny = base.dists.poisson.quantile( 2.0, -1.0 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\n\n// Degenerate distribution when `sigma = 0.0`:\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\n\n// Degenerate distribution when `sigma = 0.0`:\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n","base.dists.triangular.kurtosis":"var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n","base.dists.triangular.logcdf":"var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n","base.dists.triangular.variance":"var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n\n// Custom scale function:\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\n\n// 3*10^0 + 2*10^1 + 1*10^2\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalrational":"\n// 2x^3 + 4x^2 - 5x^1 - 6x^0\nvar P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n// 0.5x^1 + 3x^0\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n// Evaluate the rational function:\nvar v = base.evalrational( P, Q, 6.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"\n// 2^4 + 3*2^2 + 1\nvar v = base.fibpoly( 5, 2.0 )\n","base.flipsign":"var z = base.flipsign( -3.14, 10.0 )\nz = base.flipsign( -3.14, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.14, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"\n// Round to 4 decimal places:\nvar y = base.floorb( 3.14159, -4, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.floorb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two toward negative infinity:\ny = base.floorb( 5.0, 1, 2 )\n","base.floorn":"\n// Round to 4 decimal places:\nvar y = base.floorn( 3.14159, -4 )\n\n// If `n = 0`, standard round toward negative infinity behavior:\ny = base.floorn( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5 )\ny = base.floorsd( 3.14159, 1 )\ny = base.floorsd( 12368.0, 2 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.fresnel( out, 0.0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar y = base.frexp( out, 4.0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\n\n// The function handles subnormals:\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\n\n// The function handles special values:\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\n\n// The function handles subnormals:\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\n\n// The function handles special values:\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gasum":"\n// Standard usage:\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar sum = base.gasum( x.length, x, 1 )\n\n// Sum every other value:\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nsum = base.gasum( N, x, stride )\n\n// Use view offset; e.g., starting at 2nd element:\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nsum = base.gasum( N, x1, stride )\n","base.gaxpy":"\n// Standard usage:\nvar x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nvar alpha = 5.0;\nbase.gaxpy( x.length, alpha, x, 1, y, 1 )\n\n// Using `N` and `stride` parameters:\nvar N = base.floor( x.length / 2 );\nbase.gaxpy( N, alpha, x, 2, y, -1 )\n\n// Using view offsets:\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.gaxpy( N, 5.0, x1, -2, y1, 1 )\ny0\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.gcopy":"\n// Standard usage:\nvar x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.gcopy( x.length, x, 1, y, 1 )\n\n// Advanced indexing:\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nvar N = base.floor( x.length / 2 );\nbase.gcopy( N, x, -2, y, 1 )\n\n// Using typed array views:\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.gcopy( N, x1, -2, y1, 1 )\ny0\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\nout = new Array( 2 );\nvar v = base.kernelBetainc( out, 0.2, 1.0, 2.0, true, true )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"\n// 2^5 + 5*2^3 + 5*2\nvar v = base.lucaspoly( 5, 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 5.9, 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 5.9, 3.14, 4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 5.9, 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 5.9, 3.14, 4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 5.9, 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\nv = base.minmax( 3.14 )\nvar out = new Array( 2 );\nv = base.minmax( out, 3.14 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14, 4.2 )\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\nv = base.minmaxabs( 3.14 )\nvar out = new Array( 2 );\nv = base.minmaxabs( out, 3.14 )\nvar bool = ( v === out )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n\n// Provide an output array:\nvar out = new Float64Array( 2 );\nparts = base.modf( out, 3.14 )\nvar bool = ( parts === out )\n","base.ndarray":"var ctor = base.ndarray( 'float64', 3 )\n\n// To create a new instance...\nvar b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nvar v = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarrayMemoized":"var ctor = base.ndarrayMemoized( 'float64', 3 )\nvar f = base.ndarrayMemoized( 'float64', 3 )\nvar bool = ( f === ctor )\n\n// To create a new instance...\nvar b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nvar v = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n\n// Special cases:\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nvar v = base.normalize( out, 3.14e-319 )\nbool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n\n// Special cases:\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n\n// Provide an output array:\nout = new Float32Array( 2 );\nvar v = base.normalizef( out, base.float64ToFloat32( 1.401e-45 ) )\nbool = ( v === out )\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n","base.pow":"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n","base.powm1":"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n","base.rad2deg":"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\n\n// Due to finite precision, canonical values may not be returned:\nd = base.rad2deg( PI/6.0 )\n","base.ramp":"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n","base.random.arcsine":"var r = base.random.arcsine( 2.0, 5.0 )\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.beta":"var r = base.random.beta( 2.0, 5.0 );\n","base.random.betaprime":"var r = base.random.betaprime( 2.0, 5.0 );\n","base.random.binomial":"var r = base.random.binomial( 20, 0.8 );\n","base.random.boxMuller":"var r = base.random.boxMuller();\n","base.random.cauchy":"var r = base.random.cauchy( 2.0, 5.0 );\n","base.random.chi":"var r = base.random.chi( 2 );\n","base.random.chisquare":"var r = base.random.chisquare( 2 );\n","base.random.cosine":"var r = base.random.cosine( 2.0, 5.0 );\n","base.random.discreteUniform":"var r = base.random.discreteUniform( 2, 50 );\n","base.random.erlang":"var r = base.random.erlang( 2, 5.0 );\n","base.random.exponential":"var r = base.random.exponential( 7.9 );\n","base.random.f":"var r = base.random.f( 2.0, 5.0 );\n","base.random.frechet":"var r = base.random.frechet( 2.0, 5.0, 3.33 );\n","base.random.gamma":"var r = base.random.gamma( 2.0, 5.0 );\n","base.random.geometric":"var r = base.random.geometric( 0.8 );\n","base.random.gumbel":"var r = base.random.gumbel( 2.0, 5.0 );\n","base.random.hypergeometric":"var r = base.random.hypergeometric( 20, 10, 7 );\n","base.random.improvedZiggurat":"var r = base.random.improvedZiggurat();\n","base.random.invgamma":"var r = base.random.invgamma( 2.0, 5.0 );\n","base.random.kumaraswamy":"var r = base.random.kumaraswamy( 2.0, 5.0 );\n","base.random.laplace":"var r = base.random.laplace( 2.0, 5.0 );\n","base.random.levy":"var r = base.random.levy( 2.0, 5.0 );\n","base.random.logistic":"var r = base.random.logistic( 2.0, 5.0 );\n","base.random.lognormal":"var r = base.random.lognormal( 2.0, 5.0 );\n","base.random.minstd":"var r = base.random.minstd();\n","base.random.minstdShuffle":"var r = base.random.minstdShuffle();\n","base.random.mt19937":"var r = base.random.mt19937();\n","base.random.negativeBinomial":"var r = base.random.negativeBinomial( 20, 0.8 );\n","base.random.normal":"var r = base.random.normal( 2.0, 5.0 );\n","base.random.pareto1":"var r = base.random.pareto1( 2.0, 5.0 );\n","base.random.poisson":"var r = base.random.poisson( 7.9 );\n","base.random.randi":"var r = base.random.randi();\n","base.random.randn":"var r = base.random.randn();\n","base.random.randu":"var r = base.random.randu();\n","base.random.rayleigh":"var r = base.random.rayleigh( 2.5 );\n","base.random.t":"var r = base.random.t( 2.0 );\n","base.random.triangular":"var r = base.random.triangular( 2.0, 5.0, 3.33 );\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\n\n// Custom scale function:\nfunction scale( x, y ) {\n var s;\n ...\n x = base.abs( x );\n y = base.abs( y );\n ...\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n ...\n // Scale in units of epsilon:\n return s * EPS;\n};\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.rempio2":"var y = new Array( 2 );\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"\n// Round to 2 decimal places:\nvar y = base.roundb( 3.14159, -2, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.roundb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two:\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"\n// Round to 2 decimal places:\nvar y = base.roundn( 3.14159, -2 )\n\n// If `n = 0`, standard round behavior:\ny = base.roundn( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.sasum":"\n// Standard usage:\nvar x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\nvar sum = base.sasum( x.length, x, 1 )\n\n// Sum every other value:\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nsum = base.sasum( N, x, stride )\n\n// Use view offset; e.g., starting at 2nd element:\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nsum = base.sasum( N, x1, stride )\n","base.saxpy":"\n// Standard usage:\nvar x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.saxpy( x.length, alpha, x, 1, y, 1 )\n\n// Using `N` and `stride` parameters:\nvar N = base.floor( x.length / 2 );\nbase.saxpy( N, alpha, x, 2, y, -1 )\n\n// Using view offsets:\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.saxpy( N, 5.0, x1, -2, y1, 1 )\ny0\n","base.scopy":"\n// Standard usage:\nvar x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.scopy( x.length, x, 1, y, 1 )\n\n// Advanced indexing:\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.scopy( N, x, -2, y, 1 )\n\n// Using typed array views:\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.scopy( N, x1, -2, y1, 1 )\ny0\n","base.setHighWord":"\n// Set the higher order bits of `+infinity` to return `1`:\nvar high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\n\n// Special cases:\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n\n// Provide an output array:\nvar out = new Float64Array( 2 );\ny = base.sici( out, 3.0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincos( out, 0.0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincospi( out, 0.0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sumSeries":"\n// Using an ES6 generator function:\nfunction* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n};\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\n\n// Using a closure:\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n};\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\n\n// Setting an initial value for the sum:\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n\n// Changing the maximum number of terms to be summed:\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n\n// Adjusting the used tolerance:\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n\n// Provide an output array:\nvar out = new Uint32Array( 2 );\nw = base.toWords( out, 3.14e201 )\nvar bool = ( w === out )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncb":"\n// Round to 4 decimal places:\nvar y = base.truncb( 3.14159, -4, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.truncb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two toward zero:\ny = base.truncb( 5.0, 1, 2 )\n","base.truncn":"\n// Round to 4 decimal places:\nvar y = base.truncn( 3.14159, -4 )\n\n// If `n = 0`, standard round behavior:\ny = base.truncn( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5 )\ny = base.truncsd( 3.14159, 1 )\ny = base.truncsd( 12368.0, 2 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uimul":"var v = base.uimul( 10>>>0, 4>>>0 )\n","base.uimuldw":"var v = base.uimuldw( 1, 10 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\n\n// Evaluate at a pole:\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\n\n// Output group results as indices:\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\n\n// Output group results as index-element pairs:\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\n\n// Output group results as indices:\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"\n// Basic usage:\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\n\n// Output group results as indices:\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\n\n// Output group results as keys:\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\n\n// Output group results as keys:\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n})\n","Buffer":"var b = new Buffer( 4 )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"\n// Provide expected probabilities...\nvar x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p )\nout.print()\n\n// Set significance level...\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.print()\n\n// Calculate the test p-value via Monte Carlo simulation...\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts )\n\n// Verify that data comes from Poisson distribution...\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n// Generate a frequency table...\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda )\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","Complex128":"var z = new Complex128( 5.0, 3.0 )\nz.re\nz.im\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","compose":"function a( x ) {\n return 2 * x;\n}\nfunction b( x ) {\n return x + 3;\n}\nfunction c( x ) {\n return x / 5;\n}\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, 2*x );\n }\n};\nfunction b( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x+3 );\n }\n};\nfunction c( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x/5 );\n }\n};\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\n\n// Supply a position:\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\n\n// Set the `level` option to limit the copy depth:\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"\n// Basic usage:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\n\n// Limit number of concurrent invocations:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n\n// Process sequentially:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\n\n// Supply arity:\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\n\n// Provide function context:\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n};\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\n\n// Supply arity:\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\n\n// Provide function context:\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n};\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\n\n// Other ways to supply month:\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\n\n// Other ways to supply month:\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\n\n// Specify a custom separator via the `sep` option:\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\n\n// Specify a custom separator via the `sep` option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\n\n// Specify a custom separator via the `sep` option:\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj, 'a.b.c', 'beep' )\n\n// Specify an alternative separator via the sep option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\n\n// To create a key path which does not exist, set the create option to true:\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n};\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n});\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n});\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n});\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","E":"E\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","evil":"var v = evil( '5*4*3*2*1' )\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\n\n// The function overflows for large `x`:\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\n\n// The function overflows for large `x`:\nv = fastmath.asinh( 1.0e200 )\n\n// The function underflows for small `x`:\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\n\n// The function underflows for small `x`:\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\n\n// For a sufficiently large `x` and/or `y`, the function overflows:\nh = fastmath.hypot( 1.0e154, 1.0e154 )\n\n// For sufficiently small `x` and/or `y`, the function underflows:\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\n\n// Limit number of results:\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\n\n// Return both indices and values as index-value pairs:\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\n\n// Set the maximum depth:\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n\n// Deep copy:\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\n\n// Set the `depth` option to flatten to a specified depth:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\n\n// Set the `delimiter` option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\n\n// Flatten arrays:\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flignerTest":"\n// Data from Hollander & Wolfe (1973), p. 116:\nvar x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n];\nout = flignerTest( arr, { 'groups': groups })\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","Float32Array":"var arr = new Float32Array()\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"\n// Basic usage:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\n\n// Limit number of concurrent invocations:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n\n// Process sequentially:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"\n// Basic usage:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\n\n// Limit number of concurrent invocations:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n\n// Process sequentially:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, 2*x );\n }\n};\nfunction b( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x+3 );\n }\n};\nfunction c( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x/5 );\n }\n};\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\n\n// Output group results as indices:\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\n\n// Output group results as index-element pairs:\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\n\n// Output group results as indices:\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"\n// Basic usage:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\n\n// Output group results as indices:\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\n\n// Limit number of concurrent invocations:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n\n// Process sequentially:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\n\n// Output group results as keys:\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\n\n// Output group results as keys:\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServer":"\n// Basic usage:\nvar createServer = httpServer()\n\n// Provide a request callback:\nfunction onRequest( request, response ) {\n console.log( request.url );\n response.end( 'OK' );\n};\ncreateServer = httpServer( onRequest )\n\n// Specify a specific port:\nvar opts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n};\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n};\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar vec = ndarray( 'float64', 1 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n};\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar vec = ndarray( 'float64', 1 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n};\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar vec = ndarray( 'float64', 1 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar vec = ndarray( 'float64', 1 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n\n// Provide an output array:\nvar out = new Array( d.length );\ns = ind2sub( out, d, 17 )\nvar bool = ( s === out )\n","indexOf":"\n// Basic usage:\nvar arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\n\n// Using a `fromIndex`:\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\n\n// `fromIndex` which exceeds `array` length:\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\n\n// Negative `fromIndex`:\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\n\n// Negative `fromIndex` exceeding input `array` length:\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\n\n// Array-like objects:\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"\n// Create a parent constructor:\nfunction Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\n\n// Create a child constructor:\nfunction Bar() { Foo.call( this ); return this; };\n\n// Setup inheritance:\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"\n// Basic usage:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n\n// Process sequentially:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"\n// Basic usage:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n\n// Process sequentially:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_NODE":"IS_NODE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsolutePath":"\n// Windows environment:\nvar bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n\n// POSIX environment:\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 2, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n};\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n};\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n};\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonSymmetricMatrix":"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPersymmetricMatrix":"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 1, 2, 3, 1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"\n// Windows environments:\nvar bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n\n// POSIX environments:\nbool = isRelativePath( './foo/bar/baz' )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSharedArrayBuffer":"\n// Assuming an environment supports SharedArrayBuffer...\nvar bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 2, 1, -1, -2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 1, 0, 0, -1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 0, -1, 1, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSquareMatrix":"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 0, 0, 0, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymmetricMatrix":"var mat = ndarray( 'generic', 2 );\nvar M = mat( [ 0, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTruthy":"bool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n 'length': 10,\n 'byteOffset': 0,\n 'byteLength': 10,\n 'BYTES_PER_ELEMENT': 4\n})\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n\n// No scheme:\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\n\n// Illegal characters:\nbool = isURI( 'http://' )\n\n// Invalid path:\nbool = isURI( 'http:////foo.html' )\n\n// Incomplete hex escapes:\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWhitespace":"var bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterFibonacci":"var it = iterFibonacci();\nvar v = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacci":"var it = iterNonFibonacci();\nvar v = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"\n// Data from Hollander & Wolfe (1973), p. 116:\nvar x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n];\nout = kruskalTest( arr, { 'groups': groups })\n","kstest":"\n// Verify that data is drawn from a normal distribution:\nvar rnorm = base.random.normal.factory({ 'seed': 4839 });\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n// Test against N(0,1)\nvar out = kstest( x, 'normal', 0.0, 1.0 )\n\n// Test against N(3,1)\nout = kstest( x, 'normal', 3.0, 1.0 )\n\n// Verify that data is drawn from a uniform distribution:\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 })\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\n\n// Print output:\nout.print()\n\n// Set custom significance level:\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 })\n\n// Carry out one-sided hypothesis tests:\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 });\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' })\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' })\n\n// Set `sorted` option to true when data is in increasing order:\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true })\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0, 100, 6 )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n}\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"\n// Basic usage:\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n};\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n};\nmapFunAsync( fcn, 10, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n};\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n};\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\n\n// Sequential invocation:\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n};\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n};\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"\n// Basic usage:\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\n\n// Limit number of concurrent invocations:\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n\n// Process sequentially:\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"\n// Basic usage:\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\n\n// Limit number of concurrent invocations:\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n\n// Process sequentially:\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n};\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar river = data.river\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var ctor = ndarray( 'generic', 2 )\n\n// To create a new instance...\nvar b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nvar v = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarrayMemoized":"var ctor = ndarrayMemoized( 'generic', 2 )\nvar f = ndarrayMemoized( 'generic', 2 )\nvar bool = ( f === ctor )\n\n// To create a new instance...\nvar b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nvar v = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbolsIn( obj )\n","noop":"noop();\n","now":"var ts = now()\n","NUM_CPUS":"NUM_CPUS\n","Number":"var v = new Number( 5 )\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"\n// Basic usage:\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\n\n// Duplicate values:\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\n\n// Override duplicate values:\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"\n// Basic usage:\nfunction transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\n\n// Duplicate values:\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\n\n// Override duplicate values:\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","openURL":"var out = openURL( 'https://google.com' );\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"\n// Standard usage:\nvar out = pad( 'a', 5 )\n\n// Left pad:\nout = pad( 'a', 10, { 'lpad': 'b' })\n\n// Right pad:\nout = pad( 'a', 12, { 'rpad': 'b' })\n\n// Center an input string:\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\n\n// Left center:\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\n\n// Right center:\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\n\n// Output string always length `len`:\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\n\n// Pad right, trim right:\nout = pad( 'beep', 2 )\n\n// Pad left, trim left:\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\n\n// Pad both, trim both:\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\n\n// Pad both, trim both starting from left:\nout = pad( 'abcdef', 3, opts )\n\n// Pad both, trim both starting from right:\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parallel":"function done( error ) { if ( error ) { throw error; } };\nvar files = [ './a.js', './b.js' ];\nparallel( files, done );\n\n// Specify the number of workers:\nvar opts = { 'workers': 8 };\nparallel( files, opts, done );\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\n\n// Provide a reviver:\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n};\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","PATH_DELIMITER":"PATH_DELIMITER\n\n// POSIX environment:\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\n\n// Windows environment:\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\n\n// Windows environment:\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n\n// POSIX environment:\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\n x[ i ] = base.random.normal( 0.0, 1.0 );\n y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n base.sqrt( 1.0 - (rho*rho) ) );\n}\nvar out = pcorrtest( x, y )\n\n// Print output:\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n};\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\n\n// Provide plot data at instantiation:\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\n\n// Provide plot data at instantiation:\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\n\n// Array-like object:\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","prepend":"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\n\n// Array-like object:\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","push":"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\n\n// Array-like object:\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\n\n// Other ways to supply month:\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\n\n// Ties are averaged:\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\n\n// Missing values are placed last:\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","RE_BASENAME":"var base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]\n","RE_BASENAME_POSIX":"var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","RE_BASENAME_WINDOWS":"var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","RE_COLOR_HEXADECIMAL":"var bool = RE_COLOR_HEXADECIMAL.test( 'ffffff' )\nbool = RE_COLOR_HEXADECIMAL.test( '000' )\nbool = RE_COLOR_HEXADECIMAL.test( 'beep' )\n","RE_DECIMAL_NUMBER":"var bool = RE_DECIMAL_NUMBER.test( '1.234' )\nbool = RE_DECIMAL_NUMBER.test( '-1.234' )\nbool = RE_DECIMAL_NUMBER.test( '0.0' )\nbool = RE_DECIMAL_NUMBER.test( '.0' )\nbool = RE_DECIMAL_NUMBER.test( '0' )\nbool = RE_DECIMAL_NUMBER.test( 'beep' )\n\n// Create a RegExp to capture all decimal numbers:\nvar re = new RegExp( RE_DECIMAL_NUMBER.source, 'g' );\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","RE_DIRNAME":"var dir = RE_DIRNAME.exec( '/foo/bar/index.js' )[ 1 ]\n","RE_DIRNAME_POSIX":"var dir = RE_DIRNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( 'index.js' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( '.' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( './' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( '' )[ 1 ]\n","RE_DIRNAME_WINDOWS":"var dir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( 'index.js' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( '' )[ 1 ]\n","RE_EOL":"var bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","RE_EXTENDED_LENGTH_PATH":"var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = '/c/foo/bar';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = '/foo/bar';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\n","RE_EXTNAME":"var dir = RE_EXTNAME.exec( '/foo/bar/index.js' )[ 1 ]\n","RE_EXTNAME_POSIX":"var ext = RE_EXTNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( 'index.js' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( '.' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( './' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( '' )[ 1 ]\n","RE_EXTNAME_WINDOWS":"var ext = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'beep\\\\boop.' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'index.js' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( '' )[ 1 ]\n","RE_FILENAME":"var f = '/foo/bar/index.js';\nvar parts = RE_FILENAME.exec( f ).slice()\n","RE_FILENAME_POSIX":"var parts = RE_FILENAME_POSIX.exec( '/foo/bar/index.js' ).slice()\nparts = RE_FILENAME_POSIX.exec( './foo/bar/.gitignore' ).slice()\nparts = RE_FILENAME_POSIX.exec( 'foo/file.pdf' ).slice()\nparts = RE_FILENAME_POSIX.exec( '/foo/bar/file' ).slice()\nparts = RE_FILENAME_POSIX.exec( 'index.js' ).slice()\nparts = RE_FILENAME_POSIX.exec( '.' ).slice()\nparts = RE_FILENAME_POSIX.exec( './' ).slice()\nparts = RE_FILENAME_POSIX.exec( '' ).slice()\n","RE_FILENAME_WINDOWS":"var parts = RE_FILENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( 'index.js' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '.' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( './' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '' ).slice()\n","RE_FUNCTION_NAME":"function beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","RE_NATIVE_FUNCTION":"var bool = RE_NATIVE_FUNCTION.test( Date.toString() )\nbool = RE_NATIVE_FUNCTION.test( (function noop() {}).toString() )\n","RE_REGEXP":"var bool = RE_REGEXP.test( '/^beep$/' )\nbool = RE_REGEXP.test( '/boop' )\n\n// Escape regular expression strings:\nbool = RE_REGEXP.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE_REGEXP.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","RE_UNC_PATH":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE_UNC_PATH.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\';\nbool = RE_UNC_PATH.test( path )\npath = '';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE_UNC_PATH.test( path )\npath = '//server/share';\nbool = RE_UNC_PATH.test( path )\npath = '/foo/bar';\nbool = RE_UNC_PATH.test( path )\npath = 'foo/bar';\nbool = RE_UNC_PATH.test( path )\npath = './foo/bar';\nbool = RE_UNC_PATH.test( path )\npath = '/foo/../bar';\nbool = RE_UNC_PATH.test( path )\n","RE_UTF16_SURROGATE_PAIR":"var bool = RE_UTF16_SURROGATE_PAIR.test( 'abc\\uD800\\uDC00def' )\nbool = RE_UTF16_SURROGATE_PAIR.test( 'abcdef' )\n","RE_UTF16_UNPAIRED_SURROGATE":"var bool = RE_UTF16_UNPAIRED_SURROGATE.test( 'abc' )\nbool = RE_UTF16_UNPAIRED_SURROGATE.test( '\\uD800' )\n","RE_WHITESPACE":"var bool = RE_WHITESPACE.test( '\\n' )\nbool = RE_WHITESPACE.test( ' ' )\nbool = RE_WHITESPACE.test( 'a' )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadDir( './beep/boop', onRead );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadFile( './beep/boop.js', onRead );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadJSON( './beep/boop.json', onRead );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadWASM( './beep/boop.wasm', onRead );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reduce":"function sum( acc, v ) { return acc + v; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = reduce( arr, 0, sum )\n","reduceAsync":"\n// Basic usage:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n\n// Process concurrently:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceRight":"function sum( acc, v ) {\n console.log( '%s: %d', acc, v );\n return acc + v;\n};\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = reduceRight( arr, 0, sum );\nout\n","reduceRightAsync":"\n// Basic usage:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n\n// Process concurrently:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n\n// Case-insensitive:\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n};\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"\n// Standard usage:\nvar out = replace( 'beep', 'e', 'o' )\n\n// Replacer function:\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\n\n// Replace only first match:\nout = replace( 'beep', /e/, 'o' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n};\nresolveParentPath( 'package.json', onPath );\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\n\n// Set sample size:\nout = sample( [ 3, 6, 9 ], { 'size': 10 })\nout = sample( [ 0, 1 ], { 'size': 20 })\n\n// Draw without replacement:\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 })\nout = sample( [ 0, 1 ], { 'replace': false })\n\n// Assigning non-uniform element probabilities:\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs })\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false })\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"\n// Assuming an environment supports SharedArrayBuffers...\nvar buf = new SharedArrayBuffer( 5 )\n","shift":"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\n\n// Array-like object:\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' });\nvar bool = ( data === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","SOTU":"var out = SOTU()\n\n// Retrieve addresses by one or more Presidents...\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\n\n// Retrieve addresses by one or more political parties...\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\n\n// Retrieve addresses from one or more years...\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\n\n// Retrieve addresses from a range of consecutive years...\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\n\n// Provide sparkline data at instantiation:\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"\n// Basic usage:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\n\n// Limit number of concurrent invocations:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n\n// Process sequentially:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n};\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n};\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n};\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n};\nfunction y() {\n return -1.0;\n};\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n};\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\ntrythenAsync( x, y, done )\n","ttest":"\n// One-sample t-test:\nvar rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 });\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n}\nvar out = ttest( x )\n\n// Paired t-test:\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 });\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n}\nout = ttest( x, y )\n\n// Print formatted output:\nvar table = out.print()\n\n// Choose custom significance level:\narr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 });\ntable = out.print()\n\n// Test for a mean equal to five:\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 })\n\n// Perform one-sided tests:\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' });\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' });\ntable = out.print()\n","ttest2":"\n// Student's sleep data:\nvar x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\n\n// Print table output:\nvar table = out.print()\n\n// Choose a different significance level than `0.05`:\nout = ttest2( x, y, { 'alpha': 0.1 });\ntable = out.print()\n\n// Perform one-sided tests:\nout = ttest2( x, y, { 'alternative': 'less' });\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' });\ntable = out.print()\n\n// Run tests with equal variances assumption:\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' });\ntable = out.print()\n\n// Test for a difference in means besides zero:\nvar rnorm = base.random.normal.factory({ 'seed': 372 });\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n}\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n}\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' })\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayComplexCtors":"var ctor = typedarrayComplexCtors( 'complex64' )\nctor = typedarrayComplexCtors( 'float32' )\n","typedarrayComplexDataTypes":"var out = typedarrayComplexDataTypes()\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"\n// Built-ins:\nvar t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\n\n// Arguments object:\nfunction beep() { return arguments; };\nt = typeOf( beep() )\n\n// Node.js Buffer object:\nt = typeOf( new Buffer( 10 ) )\n\n// Custom constructor:\nfunction Person() { return this };\nt = typeOf( new Person() )\n\n// Anonymous constructor:\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n};\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\n\n// To enforce a fixed number of parameters, provide an `arity` argument:\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n};\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\n\n// To specify an execution context, provide a `thisArg` argument:\nfunction addX( x ) {\n this.x = x;\n return addY;\n};\nfunction addY( y ) {\n return this.x + y;\n};\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n};\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\n\n// To enforce a fixed number of parameters, provide an `arity` argument:\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n};\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\n\n// To specify an execution context, provide a `thisArg` argument:\nfunction addY( y ) {\n this.y = y;\n return addX;\n};\nfunction addX( x ) {\n return x + this.y;\n};\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n};\nunlink( './beep/boop.txt', done );\n","unshift":"\n// Arrays:\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\n\n// Array-like object:\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"\n// Basic usage:\nvar arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\n\n// Provide indices:\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\n\n// Print table output:\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n};\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","zip":"\n// Basic usage:\nvar out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n\n// Turn off truncation:\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"\n// One-sample z-test:\nvar rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 });\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n}\nvar out = ztest( x, 2.0 )\n\n// Choose custom significance level and print output:\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 });\ntable = out.print()\n\n// Test for a mean equal to five:\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 })\n\n// Perform one-sided tests:\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' })\nout = ztest( arr, 1.0, { 'alternative': 'greater' })\n","ztest2":"\n// Drawn from Normal(0,2):\nvar x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n// Drawn from Normal(1,2):\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\n\n// Print table output:\nvar table = out.print()\n\n// Choose a different significance level than `0.05`:\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 });\ntable = out.print()\n\n// Perform one-sided tests:\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' });\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' });\ntable = out.print()\n\n// Test for a difference in means besides zero:\nvar rnorm = base.random.normal.factory({ 'seed': 372 });\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n}\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n}\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 })\n"} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/repl/code-blocks/datapackage.json b/lib/node_modules/@stdlib/repl/code-blocks/datapackage.json new file mode 100644 index 000000000000..0faf1f06d843 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/datapackage.json @@ -0,0 +1,61 @@ +{ + "name": "stdlib-alias-example", + "version": "", + "title": "Standard Library Aliases and Examples", + "description": "A mapping between standard library aliases and examples.", + "resources": [ + { + "name": "stdlib-alias-example-json", + "title": "Standard Library Aliases and Examples", + "description": "A mapping between standard library aliases and examples.", + "format": "json", + "mediatype": "application/json", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.json" + }, + { + "name": "stdlib-alias-example-csv", + "title": "Standard Library Aliases and Examples", + "description": "A mapping between standard library aliases and examples.", + "format": "csv", + "mediatype": "plain/csv", + "encoding": "UTF-8", + "hash": "", + "path": "./data/data.csv", + "schema": { + "fields": [ + { + "name": "alias", + "title": "Alias", + "description": "Alias.", + "type": "string", + "format": "default" + }, + { + "name": "example", + "title": "Example", + "description": "Example.", + "type": "string", + "format": "default" + } + ] + } + } + ], + "sources": [], + "keywords": [ + "stdlib", + "namespace", + "aliases", + "example", + "eg", + "help", + "docs", + "documentation", + "repl", + "usage", + "demo" + ], + "license": "PDDL-1.0 AND CC0-1.0" +} diff --git a/lib/node_modules/@stdlib/repl/code-blocks/docs/repl.txt b/lib/node_modules/@stdlib/repl/code-blocks/docs/repl.txt new file mode 100644 index 000000000000..a0e2aa008b02 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/docs/repl.txt @@ -0,0 +1,21 @@ + +{{alias}}( alias ) + Returns an example associated with a provided alias. + + Parameters + ---------- + alias: string + Alias. + + Returns + ------- + out: string|null + Example. + + Examples + -------- + > var txt = {{alias}}( '{{alias:@stdlib/math/base/special/sin}}' ) + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/repl/code-blocks/docs/types/index.d.ts b/lib/node_modules/@stdlib/repl/code-blocks/docs/types/index.d.ts new file mode 100644 index 000000000000..7eac677a794c --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/docs/types/index.d.ts @@ -0,0 +1,35 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Returns an example associated with a specified alias. +* +* @param alias - alias +* @returns example +* +* @example +* var out = example( 'base.sin' ); +*/ +declare function example( alias: string ): string | null; + + +// EXPORTS // + +export = example; diff --git a/lib/node_modules/@stdlib/repl/code-blocks/docs/types/test.ts b/lib/node_modules/@stdlib/repl/code-blocks/docs/types/test.ts new file mode 100644 index 000000000000..e153d4adbb48 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import example = require( './index' ); + + +// TESTS // + +// The function returns a string or null... +{ + example( 'base.sin' ); // $ExpectType string | null +} + +// The compiler throws an error if the function is not provided a string... +{ + example( 5 ); // $ExpectError + example( true ); // $ExpectError + example( false ); // $ExpectError + example( null ); // $ExpectError + example( undefined ); // $ExpectError + example( [] ); // $ExpectError + example( {} ); // $ExpectError + example( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + example( 'base.sin', 'beep' ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/repl/code-blocks/docs/usage.txt b/lib/node_modules/@stdlib/repl/code-blocks/docs/usage.txt new file mode 100644 index 000000000000..064d0cdace3d --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/docs/usage.txt @@ -0,0 +1,8 @@ + +Usage: stdlib-alias-example [options] + +Options: + + -h, --help Print this message. + -V, --version Print the package version. + diff --git a/lib/node_modules/@stdlib/repl/code-blocks/etc/cli_opts.json b/lib/node_modules/@stdlib/repl/code-blocks/etc/cli_opts.json new file mode 100644 index 000000000000..92119c456962 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/etc/cli_opts.json @@ -0,0 +1,15 @@ +{ + "string": [], + "boolean": [ + "help", + "version" + ], + "alias": { + "help": [ + "h" + ], + "version": [ + "V" + ] + } +} diff --git a/lib/node_modules/@stdlib/repl/code-blocks/examples/index.js b/lib/node_modules/@stdlib/repl/code-blocks/examples/index.js index e2bee8766744..ce6a0e2fa935 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/examples/index.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/examples/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -18,8 +18,19 @@ 'use strict'; -var examples = require( './../lib' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var example = require( './../lib' ); -var db = examples(); -console.log( db ); -// => {...} +var list; +var len; +var idx; +var i; + +list = aliases(); +len = list.length; + +for ( i = 0; i < 100; i++ ) { + idx = discreteUniform( 0, len-1 ); + console.log( example( list[ idx ] ) ); +} diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js deleted file mode 100644 index e4877723fd71..000000000000 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/db.js +++ /dev/null @@ -1,1914 +0,0 @@ -/* eslint-disable quotes, max-lines */ - -/** -* @license Apache-2.0 -* -* Copyright (c) 2019 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -/* -* This file is generated by scripts/build.js. -*/ -'use strict'; - -var db = { - "AFINN_96": "list = AFINN_96()\n", - "AFINN_111": "list = AFINN_111()\n", - "alias2pkg": "v = alias2pkg( 'base.sin' )\n", - "alias2related": "v = alias2related( 'base.sin' )\n", - "aliases": "o = aliases()\n", - "allocUnsafe": "buf = allocUnsafe( 100 )\n", - "anova1": "x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nf = [\n'control', 'treatA', 'treatB', 'treatC', 'control',\n'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n];\nout = anova1( x, f )\n", - "ANSCOMBES_QUARTET": "d = ANSCOMBES_QUARTET()\n", - "any": "arr = [ 0, 0, 0, 0, 1 ];\nbool = any( arr )\n", - "anyBy": "function negative( v ) { return ( v < 0 ); };\narr = [ 1, 2, 3, 4, -1 ];\nbool = anyBy( arr, negative )\n", - "anyByAsync": "\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\narr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'series': true };\narr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n", - "anyByRight": "function negative( v ) { return ( v < 0 ); };\narr = [ -1, 1, 2, 3, 4 ];\nbool = anyByRight( arr, negative )\n", - "anyByRightAsync": "\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\narr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'limit': 2 };\narr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'series': true };\narr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n", - "APERY": "APERY\n", - "append": "\n// Arrays:\narr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\n\n// Array-like object:\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n", - "ARCH": "ARCH\n", - "argumentFunction": "argn = argumentFunction( 1 );\nv = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n", - "ARGV": "execPath = ARGV[ 0 ]\n", - "array": "\n// Create a 2x2 matrix:\narr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n\n// Get an element using subscripts:\nv = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n", - "array2buffer": "buf = array2buffer( [ 1, 2, 3, 4 ] )\n", - "array2iterator": "it = array2iterator( [ 1, 2, 3, 4 ] );\nv = it.next().value\nv = it.next().value\n", - "array2iteratorRight": "it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nv = it.next().value\nv = it.next().value\n", - "ArrayBuffer": "buf = new ArrayBuffer( 5 )\n", - "arraybuffer2buffer": "ab = new ArrayBuffer( 10 )\nbuf = arraybuffer2buffer( ab )\nlen = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n", - "arrayCtors": "ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n", - "arrayDataType": "arr = new Float64Array( 10 );\ndt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n", - "arrayDataTypes": "out = arrayDataTypes()\n", - "arrayMinDataType": "dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n", - "arrayNextDataType": "out = arrayNextDataType( 'float32' )\n", - "arrayPromotionRules": "out = arrayPromotionRules( 'float32', 'int32' )\n", - "arraySafeCasts": "out = arraySafeCasts( 'float32' )\n", - "arraySameKindCasts": "out = arraySameKindCasts( 'float32' )\n", - "arrayShape": "out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n", - "arrayStream": "function fcn( chunk ) { console.log( chunk.toString() ); };\ns = arrayStream( [ 1, 2, 3 ] );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "arrayview2iterator": "it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nv = it.next().value\nv = it.next().value\n", - "arrayview2iteratorRight": "it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nv = it.next().value\nv = it.next().value\n", - "AsyncIteratorSymbol": "s = AsyncIteratorSymbol\n", - "bartlettTest": "\n// Data from Hollander & Wolfe (1973), p. 116:\nx = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\ny = [ 3.8, 2.7, 4.0, 2.4 ];\nz = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nout = bartlettTest( x, y, z )\narr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n];\ngroups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n];\nout = bartlettTest( arr, { 'groups': groups })\n", - "base.abs": "y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n", - "base.abs2": "y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n", - "base.absdiff": "d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n", - "base.absInt32": "v = base.absInt32( -1|0 )\nv = base.absInt32( 2|0 )\nv = base.absInt32( 0|0 )\n", - "base.acos": "y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n", - "base.acosh": "y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n", - "base.acoth": "y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n", - "base.acovercos": "y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n", - "base.acoversin": "y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n", - "base.ahavercos": "y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n", - "base.ahaversin": "y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n", - "base.asin": "y = base.asin( 0.0 )\ny = base.asin( PI/2.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n", - "base.asinh": "y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n", - "base.atan": "y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n", - "base.atan2": "v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n", - "base.atanh": "y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n", - "base.avercos": "y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n", - "base.aversin": "y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n", - "base.bernoulli": "y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n", - "base.besselj0": "y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n", - "base.besselj1": "y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n", - "base.bessely0": "y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n", - "base.bessely1": "y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n", - "base.beta": "v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n", - "base.betainc": "y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n", - "base.betaincinv": "y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n", - "base.betaln": "v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n", - "base.binet": "y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n", - "base.binomcoef": "v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n", - "base.binomcoefln": "v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n", - "base.boxcox": "v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n", - "base.boxcox1p": "v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n", - "base.boxcox1pinv": "v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n", - "base.boxcoxinv": "v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n", - "base.cabs": "y = base.cabs( 5.0, 3.0 )\n", - "base.cabs2": "y = base.cabs2( 5.0, 3.0 )\n", - "base.cadd": "y = base.cadd( 5.0, 3.0, -2.0, 1.0 )\n\n// Provide an output array:\nout = new Float32Array( 2 );\ny = base.cadd( out, 5.0, 3.0, -2.0, 1.0 )\nbool = ( y === out )\n", - "base.cbrt": "y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n", - "base.cceil": "out = base.cceil( 5.5, 3.3 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.cceil( out, 5.5, 3.3 )\nbool = ( v === out )\n", - "base.cceiln": "out = base.cceiln( 5.555, -3.333, -2 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.cceiln( out, 5.555, -3.333, -2 )\nbool = ( v === out )\n", - "base.ccis": "y = base.ccis( 0.0, 0.0 )\ny = base.ccis( 1.0, 0.0 )\nout = new Float64Array( 2 );\nv = base.ccis( out, 1.0, 0.0 )\nbool = ( v === out )\n", - "base.cdiv": "y = base.cdiv( -13.0, -1.0, -2.0, 1.0 )\nout = new Float64Array( 2 );\nv = base.cdiv( out, -13.0, -1.0, -2.0, 1.0 )\nbool = ( v === out )\n", - "base.ceil": "y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n", - "base.ceil2": "y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n", - "base.ceil10": "y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n", - "base.ceilb": "\n// Round to 4 decimal places:\ny = base.ceilb( 3.14159, -4, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.ceilb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two toward positive infinity:\ny = base.ceilb( 5.0, 1, 2 )\n", - "base.ceiln": "\n// Round to 2 decimal places:\ny = base.ceiln( 3.14159, -2 )\n\n// If `n = 0`, standard round toward positive infinity behavior:\ny = base.ceiln( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.ceiln( 12368.0, 3 )\n", - "base.ceilsd": "y = base.ceilsd( 3.14159, 5 )\ny = base.ceilsd( 3.14159, 1 )\ny = base.ceilsd( 12368.0, 2 )\ny = base.ceilsd( 0.0313, 2, 2 )\n", - "base.cexp": "y = base.cexp( 0.0, 0.0 )\ny = base.cexp( 0.0, 1.0 )\nout = new Float64Array( 2 );\nv = base.cexp( out, 0.0, 1.0 )\nbool = ( v === out )\n", - "base.cflipsign": "out = base.cflipsign( -4.2, 5.5, -9 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.cflipsign( out, -4.2, 5.5, 8 )\nbool = ( v === out )\n", - "base.cfloor": "out = base.cfloor( 5.5, 3.3 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.cfloor( out, 5.5, 3.3 )\nbool = ( v === out )\n", - "base.cfloorn": "out = base.cfloorn( 5.555, -3.333, -2 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.cfloorn( out, 5.555, -3.333, -2 )\nbool = ( v === out )\n", - "base.cinv": "y = base.cinv( 2.0, 4.0 )\nout = new Float64Array( 2 );\nv = base.cinv( out, 2.0, 4.0 )\nbool = ( v === out )\n", - "base.clamp": "y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n", - "base.cmul": "out = base.cmul( 5.0, 3.0, -2.0, 1.0 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.cmul( out, 5.0, 3.0, -2.0, 1.0 )\nbool = ( v === out )\n", - "base.cneg": "out = base.cneg( -4.2, 5.5 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.cneg( out, -4.2, 5.5 )\nbool = ( v === out )\n", - "base.continuedFraction": "\n// Continued fraction for (e-1)^(-1):\nfunction closure() {\n var i = 0;\n return function() {\n i += 1;\n return [ i, i ];\n };\n};\ngen = closure();\nout = base.continuedFraction( gen )\n\n// Using an ES6 generator:\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n};\ngen = generator();\nout = base.continuedFraction( gen )\n\n// Set options:\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n", - "base.copysign": "z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n", - "base.cos": "y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n", - "base.cosh": "y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n", - "base.cosm1": "y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n", - "base.cospi": "y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n", - "base.covercos": "y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n", - "base.coversin": "y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n", - "base.cphase": "phi = base.cphase( 5.0, 3.0 )\n", - "base.cpolar": "out = base.cpolar( 5.0, 3.0 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.cpolar( out, 5.0, 3.0 )\nbool = ( v === out )\n", - "base.cround": "out = base.cround( 5.5, 3.3 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.cround( out, 5.5, 3.3 )\nbool = ( v === out )\n", - "base.croundn": "out = base.croundn( 5.555, -3.336, -2 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.croundn( out, 5.555, -3.336, -2 )\nbool = ( v === out )\n", - "base.csignum": "out = base.csignum( -4.2, 5.5 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.csignum( out, -4.2, 5.5 )\nbool = ( v === out )\n", - "base.csub": "out = base.csub( 5.0, 3.0, -2.0, 1.0 )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.csub( out, 5.0, 3.0, -2.0, 1.0 )\nbool = ( v === out )\n", - "base.dasum": "\n// Standard usage:\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\nsum = base.dasum( x.length, x, 1 )\n\n// Sum every other value:\nN = base.floor( x.length / 2 );\nstride = 2;\nsum = base.dasum( N, x, stride )\n\n// Use view offset; e.g., starting at 2nd element:\nx0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nx1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nsum = base.dasum( N, x1, stride )\n", - "base.daxpy": "\n// Standard usage:\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nalpha = 5.0;\nbase.daxpy( x.length, alpha, x, 1, y, 1 )\n\n// Using `N` and `stride` parameters:\nN = base.floor( x.length / 2 );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.daxpy( N, alpha, x, 2, y, -1 )\n\n// Using view offsets:\nx0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nx1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ny1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.daxpy( N, 5.0, x1, -2, y1, 1 )\ny0\n", - "base.dcopy": "\n// Standard usage:\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\ny = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.dcopy( x.length, x, 1, y, 1 )\n\n// Advanced indexing:\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nN = base.floor( x.length / 2 );\nbase.dcopy( N, x, -2, y, 1 )\n\n// Using typed array views:\nx0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nx1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ny1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.dcopy( N, x1, -2, y1, 1 )\ny0\n", - "base.deg2rad": "r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n", - "base.digamma": "y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n", - "base.diracDelta": "y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n", - "base.dists.arcsine.Arcsine": "arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n", - "base.dists.arcsine.cdf": "y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n", - "base.dists.arcsine.entropy": "v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n", - "base.dists.arcsine.kurtosis": "v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n", - "base.dists.arcsine.logcdf": "y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n", - "base.dists.arcsine.logpdf": "y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n", - "base.dists.arcsine.mean": "v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n", - "base.dists.arcsine.median": "v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n", - "base.dists.arcsine.mode": "v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n", - "base.dists.arcsine.pdf": "y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n", - "base.dists.arcsine.quantile": "y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n", - "base.dists.arcsine.skewness": "v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n", - "base.dists.arcsine.stdev": "v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n", - "base.dists.arcsine.variance": "v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n", - "base.dists.bernoulli.Bernoulli": "bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n", - "base.dists.bernoulli.cdf": "y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\n\n// Invalid probability:\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n", - "base.dists.bernoulli.entropy": "v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n", - "base.dists.bernoulli.kurtosis": "v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n", - "base.dists.bernoulli.mean": "v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n", - "base.dists.bernoulli.median": "v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n", - "base.dists.bernoulli.mgf": "y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n", - "base.dists.bernoulli.mode": "v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n", - "base.dists.bernoulli.pmf": "y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\n\n// Invalid success probability:\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n", - "base.dists.bernoulli.quantile": "y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n", - "base.dists.bernoulli.skewness": "v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n", - "base.dists.bernoulli.stdev": "v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n", - "base.dists.bernoulli.variance": "v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n", - "base.dists.beta.Beta": "beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n", - "base.dists.beta.cdf": "y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n", - "base.dists.beta.entropy": "v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n", - "base.dists.beta.kurtosis": "v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n", - "base.dists.beta.logcdf": "y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n", - "base.dists.beta.logpdf": "y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n", - "base.dists.beta.mean": "v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n", - "base.dists.beta.median": "v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n", - "base.dists.beta.mgf": "y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n", - "base.dists.beta.mode": "v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n", - "base.dists.beta.pdf": "y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n", - "base.dists.beta.quantile": "y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n", - "base.dists.beta.skewness": "v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n", - "base.dists.beta.stdev": "v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n", - "base.dists.beta.variance": "v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n", - "base.dists.betaprime.BetaPrime": "betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n", - "base.dists.betaprime.cdf": "y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n", - "base.dists.betaprime.kurtosis": "v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n", - "base.dists.betaprime.logcdf": "y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n", - "base.dists.betaprime.logpdf": "y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n", - "base.dists.betaprime.mean": "v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n", - "base.dists.betaprime.mode": "v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n", - "base.dists.betaprime.pdf": "y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n", - "base.dists.betaprime.quantile": "y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n", - "base.dists.betaprime.skewness": "v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n", - "base.dists.betaprime.stdev": "v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n", - "base.dists.betaprime.variance": "v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n", - "base.dists.binomial.Binomial": "binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n", - "base.dists.binomial.cdf": "y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n", - "base.dists.binomial.entropy": "v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n", - "base.dists.binomial.kurtosis": "v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n", - "base.dists.binomial.logpmf": "y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n", - "base.dists.binomial.mean": "v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n", - "base.dists.binomial.median": "v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n", - "base.dists.binomial.mgf": "y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n", - "base.dists.binomial.mode": "v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n", - "base.dists.binomial.pmf": "y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n", - "base.dists.binomial.quantile": "y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n", - "base.dists.binomial.skewness": "v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n", - "base.dists.binomial.stdev": "v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n", - "base.dists.binomial.variance": "v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n", - "base.dists.cauchy.Cauchy": "cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n", - "base.dists.cauchy.cdf": "y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n", - "base.dists.cauchy.entropy": "v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n", - "base.dists.cauchy.logcdf": "y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n", - "base.dists.cauchy.logpdf": "y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n", - "base.dists.cauchy.median": "v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n", - "base.dists.cauchy.mode": "v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n", - "base.dists.cauchy.pdf": "y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n", - "base.dists.cauchy.quantile": "y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n", - "base.dists.chi.cdf": "y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chi.cdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n", - "base.dists.chi.Chi": "chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n", - "base.dists.chi.entropy": "v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n", - "base.dists.chi.kurtosis": "v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n", - "base.dists.chi.logpdf": "y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chi.logpdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n", - "base.dists.chi.mean": "v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n", - "base.dists.chi.mode": "v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n", - "base.dists.chi.pdf": "y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chi.pdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n", - "base.dists.chi.quantile": "y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chi.quantile( 0.5, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n", - "base.dists.chi.skewness": "v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n", - "base.dists.chi.stdev": "v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n", - "base.dists.chi.variance": "v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n", - "base.dists.chisquare.cdf": "y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n", - "base.dists.chisquare.ChiSquare": "chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n", - "base.dists.chisquare.entropy": "v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n", - "base.dists.chisquare.kurtosis": "v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n", - "base.dists.chisquare.logpdf": "y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n", - "base.dists.chisquare.mean": "v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n", - "base.dists.chisquare.mode": "v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n", - "base.dists.chisquare.pdf": "y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n", - "base.dists.chisquare.quantile": "y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\n\n// Negative degrees of freedom:\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\n\n// Degenerate distribution when `k = 0`:\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n", - "base.dists.chisquare.skewness": "v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n", - "base.dists.chisquare.stdev": "v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n", - "base.dists.chisquare.variance": "v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n", - "base.dists.cosine.cdf": "y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n\n// Degenerate distribution centered at `μ` when `s = 0.0`:\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n", - "base.dists.cosine.Cosine": "cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n", - "base.dists.cosine.kurtosis": "y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n", - "base.dists.cosine.logcdf": "y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n\n// Degenerate distribution centered at `μ` when `s = 0.0`:\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n", - "base.dists.cosine.logpdf": "y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution at `s = 0.0`:\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n", - "base.dists.cosine.mean": "y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n", - "base.dists.cosine.median": "y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n", - "base.dists.cosine.mgf": "y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n", - "base.dists.cosine.mode": "y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n", - "base.dists.cosine.pdf": "y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n", - "base.dists.cosine.quantile": "y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n", - "base.dists.cosine.skewness": "y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n", - "base.dists.cosine.stdev": "y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n", - "base.dists.cosine.variance": "y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n", - "base.dists.degenerate.cdf": "y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n", - "base.dists.degenerate.Degenerate": "degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n", - "base.dists.degenerate.entropy": "v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n", - "base.dists.degenerate.logcdf": "y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n", - "base.dists.degenerate.logpdf": "y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n", - "base.dists.degenerate.logpmf": "y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n", - "base.dists.degenerate.mean": "v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n", - "base.dists.degenerate.median": "v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n", - "base.dists.degenerate.mgf": "y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n", - "base.dists.degenerate.mode": "v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n", - "base.dists.degenerate.pdf": "y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n", - "base.dists.degenerate.pmf": "y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n", - "base.dists.degenerate.quantile": "y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n", - "base.dists.degenerate.stdev": "v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n", - "base.dists.degenerate.variance": "v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n", - "base.dists.discreteUniform.cdf": "y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n", - "base.dists.discreteUniform.DiscreteUniform": "discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n", - "base.dists.discreteUniform.kurtosis": "v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n", - "base.dists.discreteUniform.logcdf": "y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n", - "base.dists.discreteUniform.logpmf": "y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n", - "base.dists.discreteUniform.mean": "v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n", - "base.dists.discreteUniform.median": "v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n", - "base.dists.discreteUniform.mgf": "y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n", - "base.dists.discreteUniform.pmf": "y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n", - "base.dists.discreteUniform.quantile": "y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n", - "base.dists.discreteUniform.skewness": "v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n", - "base.dists.discreteUniform.stdev": "v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n", - "base.dists.discreteUniform.variance": "v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n", - "base.dists.erlang.cdf": "y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n", - "base.dists.erlang.entropy": "v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n", - "base.dists.erlang.Erlang": "erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n", - "base.dists.erlang.kurtosis": "v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n", - "base.dists.erlang.logpdf": "y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n", - "base.dists.erlang.mean": "v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n", - "base.dists.erlang.mgf": "y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n", - "base.dists.erlang.mode": "v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n", - "base.dists.erlang.pdf": "y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n", - "base.dists.erlang.quantile": "y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\n\n// Non-integer shape parameter:\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n\n// Non-positive shape parameter:\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n", - "base.dists.erlang.skewness": "v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n", - "base.dists.erlang.stdev": "v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n", - "base.dists.erlang.variance": "v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n", - "base.dists.exponential.cdf": "y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\n\n// Negative rate parameter:\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n", - "base.dists.exponential.entropy": "v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n", - "base.dists.exponential.Exponential": "exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n", - "base.dists.exponential.kurtosis": "v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n", - "base.dists.exponential.logcdf": "y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\n\n// Negative rate parameter:\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n", - "base.dists.exponential.logpdf": "y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\n\n// Negative rate:\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n", - "base.dists.exponential.mean": "v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n", - "base.dists.exponential.median": "v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n", - "base.dists.exponential.mode": "v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n", - "base.dists.exponential.pdf": "y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\n\n// Negative rate:\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n", - "base.dists.exponential.quantile": "y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\n\n// Negative rate parameter:\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n", - "base.dists.exponential.skewness": "v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n", - "base.dists.exponential.stdev": "v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n", - "base.dists.exponential.variance": "v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n", - "base.dists.f.cdf": "y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.f.cdf( 2.0, 8.0, 4.0 )\ny = base.dists.f.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.f.cdf( PINF, 4.0, 2.0 )\ny = base.dists.f.cdf( NINF, 4.0, 2.0 )\ny = base.dists.f.cdf( NaN, 1.0, 1.0 )\ny = base.dists.f.cdf( 0.0, NaN, 1.0 )\ny = base.dists.f.cdf( 0.0, 1.0, NaN )\ny = base.dists.f.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n", - "base.dists.f.entropy": "v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n", - "base.dists.f.F": "f = base.dists.f.F( 6.0, 9.0 );\nf.d1\nf.d2\nf.entropy\nf.kurtosis\nf.mean\nf.mode\nf.skewness\nf.stdev\nf.variance\nf.cdf( 3.0 )\nf.pdf( 2.5 )\nf.quantile( 0.8 )\n", - "base.dists.f.kurtosis": "v = base.dists.f.kurtosis( 3.0, 9.0 )\nv = base.dists.f.kurtosis( 4.0, 12.0 )\nv = base.dists.f.kurtosis( 8.0, 9.0 )\n", - "base.dists.f.mean": "v = base.dists.f.mean( 3.0, 5.0 )\nv = base.dists.f.mean( 4.0, 12.0 )\nv = base.dists.f.mean( 8.0, 4.0 )\n", - "base.dists.f.mode": "v = base.dists.f.mode( 3.0, 5.0 )\nv = base.dists.f.mode( 4.0, 12.0 )\nv = base.dists.f.mode( 8.0, 4.0 )\n", - "base.dists.f.pdf": "y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n", - "base.dists.f.quantile": "y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n", - "base.dists.f.skewness": "v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n", - "base.dists.f.stdev": "v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n", - "base.dists.f.variance": "v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = base.dists.f.variance( 8.0, 5.0 )\n", - "base.dists.frechet.cdf": "y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n", - "base.dists.frechet.entropy": "y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\ny = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\ny = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\ny = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n", - "base.dists.frechet.Frechet": "frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n", - "base.dists.frechet.kurtosis": "y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n", - "base.dists.frechet.logcdf": "y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n", - "base.dists.frechet.logpdf": "y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n", - "base.dists.frechet.mean": "y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n", - "base.dists.frechet.median": "y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n", - "base.dists.frechet.mode": "y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n", - "base.dists.frechet.pdf": "y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n", - "base.dists.frechet.quantile": "y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n", - "base.dists.frechet.skewness": "y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n", - "base.dists.frechet.stdev": "y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n", - "base.dists.frechet.variance": "y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n", - "base.dists.gamma.cdf": "y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0` when `α = 0.0`:\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n", - "base.dists.gamma.entropy": "v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n", - "base.dists.gamma.Gamma": "gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n", - "base.dists.gamma.kurtosis": "v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n", - "base.dists.gamma.logpdf": "y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0.0` when `α = 0.0`:\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n", - "base.dists.gamma.mean": "v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n", - "base.dists.gamma.mgf": "y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n", - "base.dists.gamma.mode": "v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n", - "base.dists.gamma.pdf": "y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0.0` when `α = 0.0`:\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n", - "base.dists.gamma.quantile": "y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n\n// Non-positive shape parameter:\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n\n// Degenerate distribution centered at `0.0` when `α = 0.0`:\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n", - "base.dists.gamma.skewness": "v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n", - "base.dists.gamma.stdev": "v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n", - "base.dists.gamma.variance": "v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n", - "base.dists.geometric.cdf": "y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\n\n// Invalid probability\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n", - "base.dists.geometric.entropy": "v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n", - "base.dists.geometric.Geometric": "geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n", - "base.dists.geometric.kurtosis": "v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n", - "base.dists.geometric.logcdf": "y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\n\n// Invalid probability\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n", - "base.dists.geometric.logpmf": "y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\n\n// Invalid success probability:\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n", - "base.dists.geometric.mean": "v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n", - "base.dists.geometric.median": "v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n", - "base.dists.geometric.mgf": "y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\n\n// Case: t >= -ln(1-p)\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n", - "base.dists.geometric.mode": "v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n", - "base.dists.geometric.pmf": "y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\n\n// Invalid success probability:\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n", - "base.dists.geometric.quantile": "y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n", - "base.dists.geometric.skewness": "v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n", - "base.dists.geometric.stdev": "v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n", - "base.dists.geometric.variance": "v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n", - "base.dists.gumbel.cdf": "y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n", - "base.dists.gumbel.entropy": "y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n", - "base.dists.gumbel.Gumbel": "gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n", - "base.dists.gumbel.kurtosis": "y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n", - "base.dists.gumbel.logcdf": "y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n", - "base.dists.gumbel.logpdf": "y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n", - "base.dists.gumbel.mean": "y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n", - "base.dists.gumbel.median": "y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n", - "base.dists.gumbel.mgf": "y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n\n// Case: `t >= 1/beta`\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n\n// Non-positive scale parameter:\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n", - "base.dists.gumbel.mode": "y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n", - "base.dists.gumbel.pdf": "y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n", - "base.dists.gumbel.quantile": "y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n", - "base.dists.gumbel.skewness": "y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n", - "base.dists.gumbel.stdev": "y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n", - "base.dists.gumbel.variance": "y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n", - "base.dists.hypergeometric.cdf": "y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n", - "base.dists.hypergeometric.Hypergeometric": "hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n", - "base.dists.hypergeometric.kurtosis": "v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n", - "base.dists.hypergeometric.logpmf": "y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n", - "base.dists.hypergeometric.mean": "v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n", - "base.dists.hypergeometric.mode": "v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n", - "base.dists.hypergeometric.pmf": "y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n", - "base.dists.hypergeometric.quantile": "y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n", - "base.dists.hypergeometric.skewness": "v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n", - "base.dists.hypergeometric.stdev": "v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n", - "base.dists.hypergeometric.variance": "v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n", - "base.dists.invgamma.cdf": "y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n", - "base.dists.invgamma.entropy": "v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n", - "base.dists.invgamma.InvGamma": "invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n", - "base.dists.invgamma.kurtosis": "v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n", - "base.dists.invgamma.logpdf": "y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n\n// Negative scale parameter:\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n", - "base.dists.invgamma.mean": "v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n", - "base.dists.invgamma.mode": "v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n", - "base.dists.invgamma.pdf": "y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n\n// Negative shape parameter:\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n\n// Negative scale parameter:\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n", - "base.dists.invgamma.quantile": "y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n\n// Non-positive shape parameter:\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n\n// Non-positive rate parameter:\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n", - "base.dists.invgamma.skewness": "v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n", - "base.dists.invgamma.stdev": "v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n", - "base.dists.invgamma.variance": "v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n", - "base.dists.kumaraswamy.cdf": "y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n", - "base.dists.kumaraswamy.Kumaraswamy": "kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n", - "base.dists.kumaraswamy.kurtosis": "v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n", - "base.dists.kumaraswamy.logcdf": "y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n", - "base.dists.kumaraswamy.logpdf": "y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n", - "base.dists.kumaraswamy.mean": "v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n", - "base.dists.kumaraswamy.median": "v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n", - "base.dists.kumaraswamy.mode": "v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n", - "base.dists.kumaraswamy.pdf": "y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n", - "base.dists.kumaraswamy.quantile": "y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n", - "base.dists.kumaraswamy.skewness": "v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n", - "base.dists.kumaraswamy.stdev": "v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n", - "base.dists.kumaraswamy.variance": "v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n", - "base.dists.laplace.cdf": "y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n", - "base.dists.laplace.entropy": "y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n", - "base.dists.laplace.kurtosis": "y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n", - "base.dists.laplace.Laplace": "laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n", - "base.dists.laplace.logcdf": "y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n", - "base.dists.laplace.logpdf": "y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n", - "base.dists.laplace.mean": "y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n", - "base.dists.laplace.median": "y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n", - "base.dists.laplace.mgf": "y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n", - "base.dists.laplace.mode": "y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n", - "base.dists.laplace.pdf": "y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n", - "base.dists.laplace.quantile": "y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n", - "base.dists.laplace.skewness": "y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n", - "base.dists.laplace.stdev": "y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n", - "base.dists.laplace.variance": "y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 )\n", - "base.dists.levy.cdf": "y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.cdf( 2, NaN, 1.0 )\ny = base.dists.levy.cdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n", - "base.dists.levy.entropy": "y = base.dists.levy.entropy( 0.0, 1.0 )\ny = base.dists.levy.entropy( 4.0, 2.0 )\ny = base.dists.levy.entropy( NaN, 1.0 )\ny = base.dists.levy.entropy( 0.0, NaN )\ny = base.dists.levy.entropy( 0.0, 0.0 )\n", - "base.dists.levy.Levy": "levy = base.dists.levy.Levy( -2.0, 3.0 );\nlevy.mu\nlevy.c\nlevy.entropy\nlevy.mean\nlevy.median\nlevy.mode\nlevy.stdev\nlevy.variance\nlevy.cdf( 0.8 )\nlevy.logcdf( 0.8 )\nlevy.logpdf( 1.0 )\nlevy.pdf( 1.0 )\nlevy.quantile( 0.8 )\n", - "base.dists.levy.logcdf": "y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 2, NaN, 1.0 )\ny = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n", - "base.dists.levy.logpdf": "y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n", - "base.dists.levy.mean": "y = base.dists.levy.mean( 0.0, 1.0 )\ny = base.dists.levy.mean( 4.0, 3.0 )\ny = base.dists.levy.mean( NaN, 1.0 )\ny = base.dists.levy.mean( 0.0, NaN )\ny = base.dists.levy.mean( 0.0, 0.0 )\n", - "base.dists.levy.median": "y = base.dists.levy.median( 0.0, 1.0 )\ny = base.dists.levy.median( 4.0, 3.0 )\ny = base.dists.levy.median( NaN, 1.0 )\ny = base.dists.levy.median( 0.0, NaN )\ny = base.dists.levy.median( 0.0, 0.0 )\n", - "base.dists.levy.mode": "y = base.dists.levy.mode( 0.0, 1.0 )\ny = base.dists.levy.mode( 4.0, 3.0 )\ny = base.dists.levy.mode( NaN, 1.0 )\ny = base.dists.levy.mode( 0.0, NaN )\ny = base.dists.levy.mode( 0.0, 0.0 )\n", - "base.dists.levy.pdf": "y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.pdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n", - "base.dists.levy.quantile": "y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.levy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.levy.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n", - "base.dists.levy.stdev": "y = base.dists.levy.stdev( 0.0, 1.0 )\ny = base.dists.levy.stdev( 4.0, 3.0 )\ny = base.dists.levy.stdev( NaN, 1.0 )\ny = base.dists.levy.stdev( 0.0, NaN )\ny = base.dists.levy.stdev( 0.0, 0.0 )\n", - "base.dists.levy.variance": "y = base.dists.levy.variance( 0.0, 1.0 )\ny = base.dists.levy.variance( 4.0, 3.0 )\ny = base.dists.levy.variance( NaN, 1.0 )\ny = base.dists.levy.variance( 0.0, NaN )\ny = base.dists.levy.variance( 0.0, 0.0 )\n", - "base.dists.logistic.cdf": "y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.cdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\ny = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n\n// Degenerate distribution centered at `μ` when `s = 0.0`:\ny = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n", - "base.dists.logistic.entropy": "y = base.dists.logistic.entropy( 0.0, 1.0 )\ny = base.dists.logistic.entropy( 4.0, 2.0 )\ny = base.dists.logistic.entropy( NaN, 1.0 )\ny = base.dists.logistic.entropy( 0.0, NaN )\ny = base.dists.logistic.entropy( 0.0, 0.0 )\n", - "base.dists.logistic.kurtosis": "y = base.dists.logistic.kurtosis( 0.0, 1.0 )\ny = base.dists.logistic.kurtosis( 4.0, 2.0 )\ny = base.dists.logistic.kurtosis( NaN, 1.0 )\ny = base.dists.logistic.kurtosis( 0.0, NaN )\ny = base.dists.logistic.kurtosis( 0.0, 0.0 )\n", - "base.dists.logistic.logcdf": "y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.logcdf( 2, NaN, 1.0 )\ny = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n", - "base.dists.logistic.Logistic": "logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\nlogistic.mu\nlogistic.s\nlogistic.entropy\nlogistic.kurtosis\nlogistic.mean\nlogistic.median\nlogistic.mode\nlogistic.skewness\nlogistic.stdev\nlogistic.variance\nlogistic.cdf( 0.8 )\nlogistic.logcdf( 0.8 )\nlogistic.logpdf( 2.0 )\nlogistic.mgf( 0.2 )\nlogistic.pdf( 2.0 )\nlogistic.quantile( 0.9 )\n", - "base.dists.logistic.logpdf": "y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution at `s = 0.0`:\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n", - "base.dists.logistic.mean": "y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n", - "base.dists.logistic.median": "y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n", - "base.dists.logistic.mgf": "y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n", - "base.dists.logistic.mode": "y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n", - "base.dists.logistic.pdf": "y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n", - "base.dists.logistic.quantile": "y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n", - "base.dists.logistic.skewness": "y = base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n", - "base.dists.logistic.stdev": "y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n", - "base.dists.logistic.variance": "y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n", - "base.dists.lognormal.cdf": "y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n", - "base.dists.lognormal.entropy": "y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n", - "base.dists.lognormal.kurtosis": "y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n", - "base.dists.lognormal.LogNormal": "lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n", - "base.dists.lognormal.logpdf": "y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n", - "base.dists.lognormal.mean": "y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n", - "base.dists.lognormal.median": "y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n", - "base.dists.lognormal.mode": "y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n", - "base.dists.lognormal.pdf": "y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n", - "base.dists.lognormal.quantile": "y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n\n// Non-positive scale parameter `σ`:\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n", - "base.dists.lognormal.skewness": "y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n", - "base.dists.lognormal.stdev": "y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n", - "base.dists.lognormal.variance": "y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n", - "base.dists.negativeBinomial.cdf": "y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n", - "base.dists.negativeBinomial.kurtosis": "v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n", - "base.dists.negativeBinomial.logpmf": "y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n", - "base.dists.negativeBinomial.mean": "v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n", - "base.dists.negativeBinomial.mgf": "y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n", - "base.dists.negativeBinomial.mode": "v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n", - "base.dists.negativeBinomial.NegativeBinomial": "nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n", - "base.dists.negativeBinomial.pmf": "y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n", - "base.dists.negativeBinomial.quantile": "y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n", - "base.dists.negativeBinomial.skewness": "v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n", - "base.dists.negativeBinomial.stdev": "v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n", - "base.dists.negativeBinomial.variance": "v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n", - "base.dists.normal.cdf": "y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n", - "base.dists.normal.entropy": "y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n", - "base.dists.normal.kurtosis": "y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n", - "base.dists.normal.logpdf": "y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n", - "base.dists.normal.mean": "y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n", - "base.dists.normal.median": "y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n", - "base.dists.normal.mgf": "y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n", - "base.dists.normal.mode": "y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n", - "base.dists.normal.Normal": "normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n", - "base.dists.normal.pdf": "y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n", - "base.dists.normal.quantile": "y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\n\n// Negative standard deviation:\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n\n// Degenerate distribution centered at `μ` when `σ = 0.0`:\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n", - "base.dists.normal.skewness": "y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n", - "base.dists.normal.stdev": "y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n", - "base.dists.normal.variance": "y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n", - "base.dists.pareto1.cdf": "y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n", - "base.dists.pareto1.entropy": "v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n", - "base.dists.pareto1.kurtosis": "v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n", - "base.dists.pareto1.logcdf": "y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n", - "base.dists.pareto1.logpdf": "y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n", - "base.dists.pareto1.mean": "v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n", - "base.dists.pareto1.median": "v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n", - "base.dists.pareto1.mode": "v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n", - "base.dists.pareto1.Pareto1": "pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n", - "base.dists.pareto1.pdf": "y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n", - "base.dists.pareto1.quantile": "y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n", - "base.dists.pareto1.skewness": "v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n", - "base.dists.pareto1.variance": "v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n", - "base.dists.poisson.cdf": "y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\n\n// Negative mean parameter:\ny = base.dists.poisson.cdf( 2.0, -1.0 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n", - "base.dists.poisson.entropy": "v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n", - "base.dists.poisson.kurtosis": "v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n", - "base.dists.poisson.logpmf": "y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\n\n// Negative mean parameter:\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n", - "base.dists.poisson.mean": "v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n", - "base.dists.poisson.median": "v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n", - "base.dists.poisson.mode": "v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n", - "base.dists.poisson.pmf": "y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\n\n// Negative mean parameter:\ny = base.dists.poisson.pmf( 2.0, -0.5 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n", - "base.dists.poisson.Poisson": "poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n", - "base.dists.poisson.quantile": "y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\n\n// Negative mean parameter:\ny = base.dists.poisson.quantile( 2.0, -1.0 )\n\n// Degenerate distribution at `λ = 0`:\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n", - "base.dists.poisson.skewness": "v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n", - "base.dists.poisson.stdev": "v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n", - "base.dists.poisson.variance": "v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n", - "base.dists.rayleigh.cdf": "y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\n\n// Degenerate distribution when `sigma = 0.0`:\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n", - "base.dists.rayleigh.entropy": "v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n", - "base.dists.rayleigh.kurtosis": "v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n", - "base.dists.rayleigh.logcdf": "y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n", - "base.dists.rayleigh.logpdf": "y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n", - "base.dists.rayleigh.mean": "v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n", - "base.dists.rayleigh.median": "v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n", - "base.dists.rayleigh.mgf": "y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n", - "base.dists.rayleigh.mode": "v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n", - "base.dists.rayleigh.pdf": "y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\n\n// Degenerate distribution when `sigma = 0.0`:\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n", - "base.dists.rayleigh.quantile": "y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\n\n// Negative scale parameter:\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n", - "base.dists.rayleigh.Rayleigh": "rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n", - "base.dists.rayleigh.skewness": "v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n", - "base.dists.rayleigh.stdev": "v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n", - "base.dists.rayleigh.variance": "v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n", - "base.dists.t.cdf": "y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n", - "base.dists.t.entropy": "v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n", - "base.dists.t.kurtosis": "v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n", - "base.dists.t.mean": "v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n", - "base.dists.t.median": "v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n", - "base.dists.t.mode": "v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n", - "base.dists.t.pdf": "y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n", - "base.dists.t.quantile": "y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n", - "base.dists.t.skewness": "v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n", - "base.dists.t.stdev": "v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n", - "base.dists.t.T": "t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n", - "base.dists.t.variance": "v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n", - "base.dists.triangular.cdf": "y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n", - "base.dists.triangular.entropy": "v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n", - "base.dists.triangular.kurtosis": "v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n", - "base.dists.triangular.logcdf": "y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n", - "base.dists.triangular.logpdf": "y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n", - "base.dists.triangular.mean": "v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n", - "base.dists.triangular.median": "v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n", - "base.dists.triangular.mgf": "y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n", - "base.dists.triangular.mode": "v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n", - "base.dists.triangular.pdf": "y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n", - "base.dists.triangular.quantile": "y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n", - "base.dists.triangular.skewness": "v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n", - "base.dists.triangular.stdev": "v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n", - "base.dists.triangular.Triangular": "triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n", - "base.dists.triangular.variance": "v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n", - "base.dists.uniform.cdf": "y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n", - "base.dists.uniform.entropy": "v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n", - "base.dists.uniform.kurtosis": "v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n", - "base.dists.uniform.logcdf": "y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n", - "base.dists.uniform.logpdf": "y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n", - "base.dists.uniform.mean": "v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n", - "base.dists.uniform.median": "v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n", - "base.dists.uniform.mgf": "y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n", - "base.dists.uniform.pdf": "y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n", - "base.dists.uniform.quantile": "y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n", - "base.dists.uniform.skewness": "v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n", - "base.dists.uniform.stdev": "v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n", - "base.dists.uniform.Uniform": "uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n", - "base.dists.uniform.variance": "v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n", - "base.dists.weibull.cdf": "y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n", - "base.dists.weibull.entropy": "v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n", - "base.dists.weibull.kurtosis": "v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n", - "base.dists.weibull.logcdf": "y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n", - "base.dists.weibull.logpdf": "y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n", - "base.dists.weibull.mean": "v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n", - "base.dists.weibull.median": "v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n", - "base.dists.weibull.mgf": "y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n", - "base.dists.weibull.mode": "v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n", - "base.dists.weibull.pdf": "y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n", - "base.dists.weibull.quantile": "y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n", - "base.dists.weibull.skewness": "v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n", - "base.dists.weibull.stdev": "v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n", - "base.dists.weibull.variance": "v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n", - "base.dists.weibull.Weibull": "weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n", - "base.ellipe": "y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n", - "base.ellipk": "y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n", - "base.epsdiff": "d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n\n// Custom scale function:\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n", - "base.erf": "y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n", - "base.erfc": "y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n", - "base.erfcinv": "y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n", - "base.erfinv": "y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n", - "base.eta": "y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n", - "base.evalpoly": "arr = [ 3.0, 2.0, 1.0 ];\n\n// 3*10^0 + 2*10^1 + 1*10^2\nv = base.evalpoly( arr, 10.0 )\n", - "base.evalrational": "\n// 2x^3 + 4x^2 - 5x^1 - 6x^0\nP = [ -6.0, -5.0, 4.0, 2.0 ];\n\n// 0.5x^1 + 3x^0\nQ = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n// Evaluate the rational function:\nv = base.evalrational( P, Q, 6.0 )\n", - "base.exp": "y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n", - "base.exp2": "y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n", - "base.exp10": "y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n", - "base.expit": "y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n", - "base.expm1": "y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n", - "base.expm1rel": "y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n", - "base.exponent": "exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n", - "base.exponentf": "exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n", - "base.factorial": "y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n", - "base.factorialln": "y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n", - "base.fallingFactorial": "v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n", - "base.fibonacci": "y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n", - "base.fibonacciIndex": "n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n", - "base.fibpoly": "\n// 2^4 + 3*2^2 + 1\nv = base.fibpoly( 5, 2.0 )\n", - "base.flipsign": "z = base.flipsign( -3.14, 10.0 )\nz = base.flipsign( -3.14, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.14, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n", - "base.float32ToInt32": "y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n", - "base.float32ToUint32": "y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n", - "base.float64ToFloat32": "y = base.float64ToFloat32( 1.337 )\n", - "base.float64ToInt32": "y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n", - "base.float64ToUint32": "y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n", - "base.floor": "y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n", - "base.floor2": "y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n", - "base.floor10": "y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n", - "base.floorb": "\n// Round to 4 decimal places:\ny = base.floorb( 3.14159, -4, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.floorb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two toward negative infinity:\ny = base.floorb( 5.0, 1, 2 )\n", - "base.floorn": "\n// Round to 4 decimal places:\ny = base.floorn( 3.14159, -4 )\n\n// If `n = 0`, standard round toward negative infinity behavior:\ny = base.floorn( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.floorn( 12368.0, 3 )\n", - "base.floorsd": "y = base.floorsd( 3.14159, 5 )\ny = base.floorsd( 3.14159, 1 )\ny = base.floorsd( 12368.0, 2 )\ny = base.floorsd( 0.0313, 2, 2 )\n", - "base.fresnel": "y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\nout = new Float64Array( 2 );\nv = base.fresnel( out, 0.0 )\nbool = ( v === out )\n", - "base.fresnelc": "y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n", - "base.fresnels": "y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n", - "base.frexp": "out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n\n// Provide an output array:\nout = new Float64Array( 2 );\ny = base.frexp( out, 4.0 )\nbool = ( y === out )\n", - "base.fromBinaryString": "bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\n\n// The function handles subnormals:\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\n\n// The function handles special values:\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n", - "base.fromBinaryStringf": "bstr = '01000000100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\n\n// The function handles subnormals:\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\n\n// The function handles special values:\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n", - "base.fromBinaryStringUint8": "bstr = '01010101';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n", - "base.fromBinaryStringUint16": "bstr = '0101010101010101';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n", - "base.fromBinaryStringUint32": "bstr = '01010101010101010101010101010101';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n", - "base.fromWordf": "word = 1068180177; // => 0 01111111 01010110010001011010001\nf32 = base.fromWordf( word ) // when printed, promoted to float64\n", - "base.fromWords": "v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n", - "base.gamma": "y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n", - "base.gamma1pm1": "y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n", - "base.gammaDeltaRatio": "y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n", - "base.gammainc": "y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n", - "base.gammaincinv": "y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n", - "base.gammaLanczosSum": "y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n", - "base.gammaLanczosSumExpGScaled": "y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n", - "base.gammaln": "y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n", - "base.gasum": "\n// Standard usage:\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nsum = base.gasum( x.length, x, 1 )\n\n// Sum every other value:\nN = base.floor( x.length / 2 );\nstride = 2;\nsum = base.gasum( N, x, stride )\n\n// Use view offset; e.g., starting at 2nd element:\nx0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nx1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nsum = base.gasum( N, x1, stride )\n", - "base.gaxpy": "\n// Standard usage:\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nalpha = 5.0;\nbase.gaxpy( x.length, alpha, x, 1, y, 1 )\n\n// Using `N` and `stride` parameters:\nN = base.floor( x.length / 2 );\nbase.gaxpy( N, alpha, x, 2, y, -1 )\n\n// Using view offsets:\nx0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nx1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ny1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.gaxpy( N, 5.0, x1, -2, y1, 1 )\ny0\n", - "base.gcd": "v = base.gcd( 48, 18 )\n", - "base.gcopy": "\n// Standard usage:\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\ny = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.gcopy( x.length, x, 1, y, 1 )\n\n// Advanced indexing:\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nN = base.floor( x.length / 2 );\nbase.gcopy( N, x, -2, y, 1 )\n\n// Using typed array views:\nx0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nx1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ny1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.gcopy( N, x1, -2, y1, 1 )\ny0\n", - "base.getHighWord": "w = base.getHighWord( 3.14e201 )\n", - "base.getLowWord": "w = base.getLowWord( 3.14e201 )\n", - "base.hacovercos": "y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n", - "base.hacoversin": "y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n", - "base.havercos": "y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n", - "base.haversin": "y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n", - "base.heaviside": "y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n", - "base.hermitepoly": "y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n", - "base.hypot": "h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n", - "base.imul": "v = base.imul( -10|0, 4|0 )\n", - "base.imuldw": "v = base.imuldw( 1, 10 )\n", - "base.int32ToUint32": "y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n", - "base.inv": "y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n", - "base.isEven": "bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n", - "base.isEvenInt32": "bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n", - "base.isFinite": "bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n", - "base.isInfinite": "bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n", - "base.isInteger": "bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n", - "base.isnan": "bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n", - "base.isNegativeInteger": "bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n", - "base.isNegativeZero": "bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n", - "base.isNonNegativeInteger": "bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n", - "base.isNonPositiveInteger": "bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n", - "base.isOdd": "bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n", - "base.isOddInt32": "bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n", - "base.isPositiveInteger": "bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n", - "base.isPositiveZero": "bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n", - "base.isPow2Uint32": "bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n", - "base.isProbability": "bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n", - "base.isSafeInteger": "bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n", - "base.kernelBetainc": "out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\nout = new Array( 2 );\nv = base.kernelBetainc( out, 0.2, 1.0, 2.0, true, true )\nbool = ( v === out )\n", - "base.kernelBetaincinv": "y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n", - "base.kernelCos": "out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n", - "base.kernelSin": "y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n", - "base.kernelTan": "out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n", - "base.kroneckerDelta": "y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n", - "base.lcm": "v = base.lcm( 21, 6 )\n", - "base.ldexp": "x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n", - "base.ln": "y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n", - "base.log": "y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n", - "base.log1mexp": "y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n", - "base.log1p": "y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n", - "base.log1pexp": "y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n", - "base.log2": "y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n", - "base.log10": "y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n", - "base.logaddexp": "v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n", - "base.logit": "y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n", - "base.lucas": "y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n", - "base.lucaspoly": "\n// 2^5 + 5*2^3 + 5*2\nv = base.lucaspoly( 5, 2.0 )\n", - "base.max": "v = base.max( 3.14, 4.2 )\nv = base.max( 5.9, 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n", - "base.maxabs": "v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 5.9, 3.14, 4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n", - "base.min": "v = base.min( 3.14, 4.2 )\nv = base.min( 5.9, 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n", - "base.minabs": "v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 5.9, 3.14, 4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n", - "base.minmax": "v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 5.9, 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\nv = base.minmax( 3.14 )\nout = new Array( 2 );\nv = base.minmax( out, 3.14 )\nbool = ( v === out )\n", - "base.minmaxabs": "v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14, 4.2 )\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\nv = base.minmaxabs( 3.14 )\nout = new Array( 2 );\nv = base.minmaxabs( out, 3.14 )\nbool = ( v === out )\n", - "base.modf": "parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nparts = base.modf( out, 3.14 )\nbool = ( parts === out )\n", - "base.ndarray": "ctor = base.ndarray( 'float64', 3 )\n\n// To create a new instance...\nb = [ 1, 2, 3, 4 ]; // underlying data buffer\nd = [ 2, 2 ]; // shape\ns = [ 2, 1 ]; // strides\no = 0; // index offset\narr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nv = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99 );\narr.get( 1, 1 )\n", - "base.ndarrayMemoized": "ctor = base.ndarrayMemoized( 'float64', 3 )\nf = base.ndarrayMemoized( 'float64', 3 )\nbool = ( f === ctor )\n\n// To create a new instance...\nb = [ 1, 2, 3, 4 ]; // underlying data buffer\nd = [ 2, 2 ]; // shape\ns = [ 2, 1 ]; // strides\no = 0; // index offset\narr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nv = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99 );\narr.get( 1, 1 )\n", - "base.negafibonacci": "y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n", - "base.negalucas": "y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n", - "base.nonfibonacci": "v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n", - "base.normalize": "out = base.normalize( 3.14e-319 )\ny = out[ 0 ];\nexponent = out[ 1 ];\nbool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n\n// Special cases:\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n\n// Provide an output array:\nout = new Float64Array( 2 );\nv = base.normalize( out, 3.14e-319 )\nbool = ( v === out )\n", - "base.normalizef": "out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\ny = out[ 0 ];\nexp = out[ 1 ];\nbool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n\n// Special cases:\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n\n// Provide an output array:\nout = new Float32Array( 2 );\nv = base.normalizef( out, base.float64ToFloat32( 1.401e-45 ) )\nbool = ( v === out )\n", - "base.normhermitepoly": "y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n", - "base.pdiff": "v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n", - "base.polygamma": "v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n", - "base.pow": "y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n", - "base.powm1": "y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n", - "base.rad2deg": "d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\n\n// Due to finite precision, canonical values may not be returned:\nd = base.rad2deg( PI/6.0 )\n", - "base.ramp": "y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n", - "base.random.arcsine": "r = base.random.arcsine( 2.0, 5.0 )\n", - "base.random.bernoulli": "r = base.random.bernoulli( 0.8 );\n", - "base.random.beta": "r = base.random.beta( 2.0, 5.0 );\n", - "base.random.betaprime": "r = base.random.betaprime( 2.0, 5.0 );\n", - "base.random.binomial": "r = base.random.binomial( 20, 0.8 );\n", - "base.random.boxMuller": "r = base.random.boxMuller();\n", - "base.random.cauchy": "r = base.random.cauchy( 2.0, 5.0 );\n", - "base.random.chi": "r = base.random.chi( 2 );\n", - "base.random.chisquare": "r = base.random.chisquare( 2 );\n", - "base.random.cosine": "r = base.random.cosine( 2.0, 5.0 );\n", - "base.random.discreteUniform": "r = base.random.discreteUniform( 2, 50 );\n", - "base.random.erlang": "r = base.random.erlang( 2, 5.0 );\n", - "base.random.exponential": "r = base.random.exponential( 7.9 );\n", - "base.random.f": "r = base.random.f( 2.0, 5.0 );\n", - "base.random.frechet": "r = base.random.frechet( 2.0, 5.0, 3.33 );\n", - "base.random.gamma": "r = base.random.gamma( 2.0, 5.0 );\n", - "base.random.geometric": "r = base.random.geometric( 0.8 );\n", - "base.random.gumbel": "r = base.random.gumbel( 2.0, 5.0 );\n", - "base.random.hypergeometric": "r = base.random.hypergeometric( 20, 10, 7 );\n", - "base.random.improvedZiggurat": "r = base.random.improvedZiggurat();\n", - "base.random.invgamma": "r = base.random.invgamma( 2.0, 5.0 );\n", - "base.random.kumaraswamy": "r = base.random.kumaraswamy( 2.0, 5.0 );\n", - "base.random.laplace": "r = base.random.laplace( 2.0, 5.0 );\n", - "base.random.levy": "r = base.random.levy( 2.0, 5.0 );\n", - "base.random.logistic": "r = base.random.logistic( 2.0, 5.0 );\n", - "base.random.lognormal": "r = base.random.lognormal( 2.0, 5.0 );\n", - "base.random.minstd": "r = base.random.minstd();\n", - "base.random.minstdShuffle": "r = base.random.minstdShuffle();\n", - "base.random.mt19937": "r = base.random.mt19937();\n", - "base.random.negativeBinomial": "r = base.random.negativeBinomial( 20, 0.8 );\n", - "base.random.normal": "r = base.random.normal( 2.0, 5.0 );\n", - "base.random.pareto1": "r = base.random.pareto1( 2.0, 5.0 );\n", - "base.random.poisson": "r = base.random.poisson( 7.9 );\n", - "base.random.randi": "r = base.random.randi();\n", - "base.random.randn": "r = base.random.randn();\n", - "base.random.randu": "r = base.random.randu();\n", - "base.random.rayleigh": "r = base.random.rayleigh( 2.5 );\n", - "base.random.t": "r = base.random.t( 2.0 );\n", - "base.random.triangular": "r = base.random.triangular( 2.0, 5.0, 3.33 );\n", - "base.random.uniform": "r = base.random.uniform( 2.0, 5.0 );\n", - "base.random.weibull": "r = base.random.weibull( 2.0, 5.0 );\n", - "base.reldiff": "d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\n\n// Custom scale function:\nfunction scale( x, y ) {\n var s;\n ...\n x = base.abs( x );\n y = base.abs( y );\n ...\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n ...\n // Scale in units of epsilon:\n return s * EPS;\n};\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n", - "base.rempio2": "y = new Array( 2 );\nn = base.rempio2( 128.0, y )\ny1 = y[ 0 ]\ny2 = y[ 1 ]\n", - "base.risingFactorial": "v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n", - "base.rotl32": "x = 2147483649;\nbStr = base.toBinaryStringUint32( x )\ny = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n", - "base.rotr32": "x = 1;\nbStr = base.toBinaryStringUint32( x )\ny = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n", - "base.round": "y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n", - "base.round2": "y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n", - "base.round10": "y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n", - "base.roundb": "\n// Round to 2 decimal places:\ny = base.roundb( 3.14159, -2, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.roundb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two:\ny = base.roundb( 5.0, 1, 2 )\n", - "base.roundn": "\n// Round to 2 decimal places:\ny = base.roundn( 3.14159, -2 )\n\n// If `n = 0`, standard round behavior:\ny = base.roundn( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.roundn( 12368.0, 3 )\n", - "base.roundsd": "y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n", - "base.rsqrt": "y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n", - "base.sasum": "\n// Standard usage:\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );\nsum = base.sasum( x.length, x, 1 )\n\n// Sum every other value:\nN = base.floor( x.length / 2 );\nstride = 2;\nsum = base.sasum( N, x, stride )\n\n// Use view offset; e.g., starting at 2nd element:\nx0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nx1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nsum = base.sasum( N, x1, stride )\n", - "base.saxpy": "\n// Standard usage:\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nalpha = 5.0;\nbase.saxpy( x.length, alpha, x, 1, y, 1 )\n\n// Using `N` and `stride` parameters:\nN = base.floor( x.length / 2 );\nbase.saxpy( N, alpha, x, 2, y, -1 )\n\n// Using view offsets:\nx0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nx1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ny1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.saxpy( N, 5.0, x1, -2, y1, 1 )\ny0\n", - "base.scopy": "\n// Standard usage:\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\ny = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.scopy( x.length, x, 1, y, 1 )\n\n// Advanced indexing:\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nN = base.floor( x.length / 2 );\nbase.scopy( N, x, -2, y, 1 )\n\n// Using typed array views:\nx0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nx1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ny1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.scopy( N, x1, -2, y1, 1 )\ny0\n", - "base.setHighWord": "\n// Set the higher order bits of `+infinity` to return `1`:\nhigh = 1072693248 >>> 0;\ny = base.setHighWord( PINF, high )\n", - "base.setLowWord": "low = 5 >>> 0;\nx = 3.14e201;\ny = base.setLowWord( x, low )\n\n// Special cases:\nlow = 12345678;\ny = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n", - "base.sici": "y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n\n// Provide an output array:\nout = new Float64Array( 2 );\ny = base.sici( out, 3.0 )\nbool = ( y === out )\n", - "base.signbit": "bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n", - "base.signbitf": "bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n", - "base.significandf": "s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n", - "base.signum": "sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n", - "base.sin": "y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n", - "base.sinc": "y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n", - "base.sincos": "y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nout = new Float64Array( 2 );\nv = base.sincos( out, 0.0 )\nbool = ( v === out )\n", - "base.sincospi": "y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\nout = new Float64Array( 2 );\nv = base.sincospi( out, 0.0 )\nbool = ( v === out )\n", - "base.sinh": "y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n", - "base.sinpi": "y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n", - "base.spence": "y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n", - "base.sqrt": "y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n", - "base.sqrt1pm1": "y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n", - "base.sumSeries": "\n// Using an ES6 generator function:\nfunction* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n};\ngen = geometricSeriesGenerator( 0.9 );\nout = base.sumSeries( gen )\n\n// Using a closure:\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n};\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\n\n// Setting an initial value for the sum:\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n\n// Changing the maximum number of terms to be summed:\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n\n// Adjusting the used tolerance:\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n", - "base.tan": "y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n", - "base.tanh": "y = base.tanh( 0.0 )\ny = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n", - "base.toBinaryString": "str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n", - "base.toBinaryStringf": "str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n", - "base.toBinaryStringUint8": "a = new Uint8Array( [ 1, 4, 9 ] );\nstr = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n", - "base.toBinaryStringUint16": "a = new Uint16Array( [ 1, 4, 9 ] );\nstr = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n", - "base.toBinaryStringUint32": "a = new Uint32Array( [ 1, 4, 9 ] );\nstr = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n", - "base.toWordf": "f32 = base.float64ToFloat32( 1.337 )\nw = base.toWordf( f32 )\n", - "base.toWords": "w = base.toWords( 3.14e201 )\n\n// Provide an output array:\nout = new Uint32Array( 2 );\nw = base.toWords( out, 3.14e201 )\nbool = ( w === out )\n", - "base.trigamma": "y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n", - "base.trunc": "y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n", - "base.trunc2": "y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n", - "base.trunc10": "y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n", - "base.truncb": "\n// Round to 4 decimal places:\ny = base.truncb( 3.14159, -4, 10 )\n\n// If `n = 0` or `b = 1`, standard round behavior:\ny = base.truncb( 3.14159, 0, 2 )\n\n// Round to nearest multiple of two toward zero:\ny = base.truncb( 5.0, 1, 2 )\n", - "base.truncn": "\n// Round to 4 decimal places:\ny = base.truncn( 3.14159, -4 )\n\n// If `n = 0`, standard round behavior:\ny = base.truncn( 3.14159, 0 )\n\n// Round to nearest thousand:\ny = base.truncn( 12368.0, 3 )\n", - "base.truncsd": "y = base.truncsd( 3.14159, 5 )\ny = base.truncsd( 3.14159, 1 )\ny = base.truncsd( 12368.0, 2 )\ny = base.truncsd( 0.0313, 2, 2 )\n", - "base.uimul": "v = base.uimul( 10>>>0, 4>>>0 )\n", - "base.uimuldw": "v = base.uimuldw( 1, 10 )\n", - "base.uint32ToInt32": "y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n", - "base.vercos": "y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n", - "base.versin": "y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n", - "base.wrap": "y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n", - "base.xlog1py": "out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n", - "base.xlogy": "out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n", - "base.zeta": "y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\n\n// Evaluate at a pole:\ny = base.zeta( 1.0 )\n", - "BERNDT_CPS_WAGES_1985": "data = BERNDT_CPS_WAGES_1985()\n", - "bifurcate": "collection = [ 'beep', 'boop', 'foo', 'bar' ];\nf = [ true, true, false, true ];\nout = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\n\n// Output group results as indices:\nf = [ true, true, false, true ];\nopts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\n\n// Output group results as index-element pairs:\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n", - "bifurcateBy": "function predicate( v ) { return v[ 0 ] === 'b'; };\ncollection = [ 'beep', 'boop', 'foo', 'bar' ];\nout = bifurcateBy( collection, predicate )\n\n// Output group results as indices:\nopts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n", - "bifurcateByAsync": "\n// Basic usage:\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\narr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\n\n// Output group results as indices:\nopts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nopts = { 'series': true };\narr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n", - "bifurcateIn": "function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nobj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nout = bifurcateIn( obj, predicate )\n\n// Output group results as keys:\nopts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n", - "bifurcateOwn": "function predicate( v ) { return v[ 0 ] === 'b'; };\nobj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nout = bifurcateOwn( obj, predicate )\n\n// Output group results as keys:\nopts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n", - "binomialTest": "out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n})\n", - "Buffer": "b = new Buffer( 4 )\n", - "buffer2json": "buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\njson = buffer2json( buf )\n", - "capitalize": "out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n", - "capitalizeKeys": "obj = { 'aa': 1, 'bb': 2 };\nout = capitalizeKeys( obj )\n", - "CATALAN": "CATALAN\n", - "CBRT_EPS": "CBRT_EPS\n", - "chdir": "err = chdir( '/path/to/current/working/directory' )\n", - "chi2gof": "\n// Provide expected probabilities...\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nout = chi2gof( x, p )\nout.print()\n\n// Set significance level...\nopts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.print()\n\n// Calculate the test p-value via Monte Carlo simulation...\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts )\n\n// Verify that data comes from Poisson distribution...\nlambda = 3.0;\nrpois = base.random.poisson.factory( lambda );\nlen = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n// Generate a frequency table...\nfreqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda )\n", - "circarray2iterator": "it = circarray2iterator( [ 1, 2, 3, 4 ] );\nv = it.next().value\nv = it.next().value\n", - "circularArrayStream": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 15 };\ns = circularArrayStream( [ 1, 2, 3 ], opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "CircularBuffer": "b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n", - "CMUDICT": "data = CMUDICT();\ndict = data.dict\nphones = data.phones\nsymbols = data.symbols\nvp = data.vp\n", - "complex": "z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n", - "Complex64": "z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n", - "COMPLEX64_NUM_BYTES": "COMPLEX64_NUM_BYTES\n", - "Complex128": "z = new Complex128( 5.0, 3.0 )\nz.re\nz.im\n", - "COMPLEX128_NUM_BYTES": "COMPLEX128_NUM_BYTES\n", - "compose": "function a( x ) {\n return 2 * x;\n}\nfunction b( x ) {\n return x + 3;\n}\nfunction c( x ) {\n return x / 5;\n}\nf = compose( c, b, a );\nz = f( 6 )\n", - "composeAsync": "function a( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, 2*x );\n }\n};\nfunction b( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x+3 );\n }\n};\nfunction c( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x/5 );\n }\n};\nf = composeAsync( c, b, a );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nf( 6, done )\n", - "configdir": "dir = configdir()\ndir = configdir( 'appname/config' )\n", - "conj": "z = new Complex128( 5.0, 3.0 );\nz.toString()\nv = conj( z );\nv.toString()\n", - "constantFunction": "fcn = constantFunction( 3.14 );\nv = fcn()\nv = fcn()\nv = fcn()\n", - "constantStream": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = constantStream( 'beep', opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "constructorName": "v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n", - "contains": "bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\n\n// Supply a position:\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n", - "convertArray": "arr = [ 1.0, 2.0, 3.0, 4.0 ];\nout = convertArray( arr, 'float32' )\n", - "convertArraySame": "x = [ 1.0, 2.0, 3.0, 4.0 ];\ny = new Float32Array( 0 );\nout = convertArraySame( x, y )\n", - "convertPath": "out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n", - "copy": "value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n\n// Set the `level` option to limit the copy depth:\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n", - "copyBuffer": "b1 = array2buffer( [ 1, 2, 3, 4 ] );\nb2 = copyBuffer( b1 )\n", - "countBy": "function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\ncollection = [ 'beep', 'boop', 'foo', 'bar' ];\nout = countBy( collection, indicator )\n", - "countByAsync": "\n// Basic usage:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\narr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\n\n// Limit number of concurrent invocations:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n\n// Process sequentially:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nopts = { 'series': true };\narr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n", - "curry": "function add( x, y ) { return x + y; };\nf = curry( add );\nsum = f( 2 )( 3 )\n\n// Supply arity:\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\n\n// Provide function context:\nobj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n};\nf = curry( obj.greet, obj );\nstr = f( 'Hello' )( 'there' )\n", - "curryRight": "function add( x, y ) { return x + y; };\nf = curryRight( add );\nsum = f( 2 )( 3 )\n\n// Supply arity:\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\n\n// Provide function context:\nobj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n};\nf = curryRight( obj.greet, obj );\nstr = f( 'there' )( 'Hello' )\n", - "cwd": "dir = cwd()\n", - "DALE_CHALL_NEW": "list = DALE_CHALL_NEW()\n", - "datasets": "out = datasets( 'MONTH_NAMES_EN' )\nopts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n", - "dayOfQuarter": "day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\n\n// Other ways to supply month:\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n", - "dayOfYear": "day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\n\n// Other ways to supply month:\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n", - "daysInMonth": "num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n", - "daysInYear": "num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n", - "debugSinkStream": "s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n", - "debugStream": "s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n", - "deepEqual": "bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n", - "deepGet": "obj = { 'a': { 'b': { 'c': 'd' } } };\nval = deepGet( obj, 'a.b.c' )\n\n// Specify a custom separator via the `sep` option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nval = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n", - "deepHasOwnProp": "obj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a.b.c' )\n\n// Specify a custom separator via the `sep` option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n", - "deepHasProp": "function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nobj = { 'a': new Foo() };\nbool = deepHasProp( obj, 'a.b.c' )\n\n// Specify a custom separator via the `sep` option:\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n", - "deepPluck": "arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n];\nout = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n];\nout = deepPluck( arr, [ 'a', 1 ] )\n", - "deepSet": "obj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a.b.c', 'beep' )\n\n// Specify an alternative separator via the sep option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\n\n// To create a key path which does not exist, set the create option to true:\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n", - "defineMemoizedProperty": "obj = {};\nfunction foo() {\n return 'bar';\n};\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n});\nobj.foo\n", - "defineProperties": "obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n});\nobj.foo\nobj.baz\n", - "defineProperty": "obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n});\nobj.foo = 'boop';\nobj\n", - "dirname": "dir = dirname( './foo/bar/index.js' )\n", - "DoublyLinkedList": "list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n", - "doUntil": "function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n", - "doUntilAsync": "function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\ndoUntilAsync( fcn, predicate, done )\n", - "doUntilEach": "function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\narr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n", - "doUntilEachRight": "function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\narr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n", - "doWhile": "function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n", - "doWhileAsync": "function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\ndoWhileAsync( fcn, predicate, done )\n", - "doWhileEach": "function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\narr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n", - "doWhileEachRight": "function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\narr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n", - "E": "E\n", - "emptyStream": "function fcn( chunk ) { console.log( chunk.toString() ); };\ns = emptyStream();\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "endsWith": "bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n", - "enumerableProperties": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\nprops = enumerableProperties( obj )\n", - "enumerablePropertiesIn": "props = enumerablePropertiesIn( [] )\n", - "enumerablePropertySymbols": "obj = {};\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nsym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nsymbols = enumerablePropertySymbols( obj )\n", - "enumerablePropertySymbolsIn": "obj = {};\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nsym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nsymbols = enumerablePropertySymbolsIn( obj )\n", - "ENV": "user = ENV.USER\n", - "EPS": "EPS\n", - "error2json": "err = new Error( 'beep' );\njson = error2json( err )\n", - "EULERGAMMA": "EULERGAMMA\n", - "every": "arr = [ 1, 1, 1, 1, 1 ];\nbool = every( arr )\n", - "everyBy": "function positive( v ) { return ( v > 0 ); };\narr = [ 1, 2, 3, 4 ];\nbool = everyBy( arr, positive )\n", - "everyByAsync": "\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\narr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'series': true };\narr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n", - "everyByRight": "function positive( v ) { return ( v > 0 ); };\narr = [ 1, 2, 3, 4 ];\nbool = everyByRight( arr, positive )\n", - "everyByRightAsync": "\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\narr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'limit': 2 };\narr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'series': true };\narr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n", - "evil": "v = evil( '5*4*3*2*1' )\n", - "exists": "function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n", - "expandContractions": "str = 'I won\\'t be able to get y\\'all out of this one.';\nout = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n", - "extname": "ext = extname( 'index.js' )\n", - "fastmath.abs": "v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n", - "fastmath.acosh": "v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\n\n// The function overflows for large `x`:\nv = fastmath.acosh( 1.0e308 )\n", - "fastmath.ampbm": "h = fastmath.ampbm( 5.0, 12.0 )\n", - "fastmath.asinh": "v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\n\n// The function overflows for large `x`:\nv = fastmath.asinh( 1.0e200 )\n\n// The function underflows for small `x`:\nv = fastmath.asinh( 1.0e-50 )\n", - "fastmath.atanh": "v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\n\n// The function underflows for small `x`:\nv = fastmath.atanh( 1.0e-17 )\n", - "fastmath.hypot": "h = fastmath.hypot( -5.0, 12.0 )\n\n// For a sufficiently large `x` and/or `y`, the function overflows:\nh = fastmath.hypot( 1.0e154, 1.0e154 )\n\n// For sufficiently small `x` and/or `y`, the function underflows:\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n", - "fastmath.log2Uint32": "v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n", - "fastmath.max": "v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n", - "fastmath.min": "v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n", - "fastmath.powint": "v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n", - "fastmath.sqrtUint32": "v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n", - "FEMALE_FIRST_NAMES_EN": "list = FEMALE_FIRST_NAMES_EN()\n", - "FIFO": "q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n", - "find": "data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvals = find( data, condition )\n\n// Limit number of results:\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\n\n// Return both indices and values as index-value pairs:\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n", - "flattenArray": "arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr )\n\n// Set the maximum depth:\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n\n// Deep copy:\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n", - "flattenObject": "obj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj )\n\n// Set the `depth` option to flatten to a specified depth:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nbool = ( obj.a.b === out[ 'a.b' ] )\n\n// Set the `delimiter` option:\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\n\n// Flatten arrays:\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n", - "flignerTest": "\n// Data from Hollander & Wolfe (1973), p. 116:\nx = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\ny = [ 3.8, 2.7, 4.0, 2.4 ];\nz = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nout = flignerTest( x, y, z )\narr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n];\ngroups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n];\nout = flignerTest( arr, { 'groups': groups })\n", - "FLOAT16_CBRT_EPS": "FLOAT16_CBRT_EPS\n", - "FLOAT16_EPS": "FLOAT16_EPS\n", - "FLOAT16_EXPONENT_BIAS": "FLOAT16_EXPONENT_BIAS\n", - "FLOAT16_MAX": "FLOAT16_MAX\n", - "FLOAT16_MAX_SAFE_INTEGER": "FLOAT16_MAX_SAFE_INTEGER\n", - "FLOAT16_MIN_SAFE_INTEGER": "FLOAT16_MIN_SAFE_INTEGER\n", - "FLOAT16_NINF": "FLOAT16_NINF\n", - "FLOAT16_NUM_BYTES": "FLOAT16_NUM_BYTES\n", - "FLOAT16_PINF": "FLOAT16_PINF\n", - "FLOAT16_PRECISION": "FLOAT16_PRECISION\n", - "FLOAT16_SMALLEST_NORMAL": "FLOAT16_SMALLEST_NORMAL\n", - "FLOAT16_SMALLEST_SUBNORMAL": "FLOAT16_SMALLEST_SUBNORMAL\n", - "FLOAT16_SQRT_EPS": "FLOAT16_SQRT_EPS\n", - "FLOAT32_CBRT_EPS": "FLOAT32_CBRT_EPS\n", - "FLOAT32_EPS": "FLOAT32_EPS\n", - "FLOAT32_EXPONENT_BIAS": "FLOAT32_EXPONENT_BIAS\n", - "FLOAT32_MAX": "FLOAT32_MAX\n", - "FLOAT32_MAX_SAFE_INTEGER": "FLOAT32_MAX_SAFE_INTEGER\n", - "FLOAT32_MIN_SAFE_INTEGER": "FLOAT32_MIN_SAFE_INTEGER\n", - "FLOAT32_NINF": "FLOAT32_NINF\n", - "FLOAT32_NUM_BYTES": "FLOAT32_NUM_BYTES\n", - "FLOAT32_PINF": "FLOAT32_PINF\n", - "FLOAT32_PRECISION": "FLOAT32_PRECISION\n", - "FLOAT32_SMALLEST_NORMAL": "FLOAT32_SMALLEST_NORMAL\n", - "FLOAT32_SMALLEST_SUBNORMAL": "FLOAT32_SMALLEST_SUBNORMAL\n", - "FLOAT32_SQRT_EPS": "FLOAT32_SQRT_EPS\n", - "Float32Array": "arr = new Float32Array()\n", - "FLOAT64_EXPONENT_BIAS": "FLOAT64_EXPONENT_BIAS\n", - "FLOAT64_HIGH_WORD_EXPONENT_MASK": "FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n", - "FLOAT64_HIGH_WORD_SIGNIFICAND_MASK": "FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n", - "FLOAT64_MAX": "FLOAT64_MAX\n", - "FLOAT64_MAX_BASE2_EXPONENT": "FLOAT64_MAX_BASE2_EXPONENT\n", - "FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL": "FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n", - "FLOAT64_MAX_BASE10_EXPONENT": "FLOAT64_MAX_BASE10_EXPONENT\n", - "FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL": "FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n", - "FLOAT64_MAX_LN": "FLOAT64_MAX_LN\n", - "FLOAT64_MAX_SAFE_FIBONACCI": "FLOAT64_MAX_SAFE_FIBONACCI\n", - "FLOAT64_MAX_SAFE_INTEGER": "FLOAT64_MAX_SAFE_INTEGER\n", - "FLOAT64_MAX_SAFE_LUCAS": "FLOAT64_MAX_SAFE_LUCAS\n", - "FLOAT64_MAX_SAFE_NTH_FIBONACCI": "FLOAT64_MAX_SAFE_NTH_FIBONACCI\n", - "FLOAT64_MAX_SAFE_NTH_LUCAS": "FLOAT64_MAX_SAFE_NTH_LUCAS\n", - "FLOAT64_MIN_BASE2_EXPONENT": "FLOAT64_MIN_BASE2_EXPONENT\n", - "FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL": "FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n", - "FLOAT64_MIN_BASE10_EXPONENT": "FLOAT64_MIN_BASE10_EXPONENT\n", - "FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL": "FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n", - "FLOAT64_MIN_LN": "FLOAT64_MIN_LN\n", - "FLOAT64_MIN_SAFE_INTEGER": "FLOAT64_MIN_SAFE_INTEGER\n", - "FLOAT64_NUM_BYTES": "FLOAT64_NUM_BYTES\n", - "FLOAT64_PRECISION": "FLOAT64_PRECISION\n", - "FLOAT64_SMALLEST_NORMAL": "FLOAT64_SMALLEST_NORMAL\n", - "FLOAT64_SMALLEST_SUBNORMAL": "FLOAT64_SMALLEST_SUBNORMAL\n", - "Float64Array": "arr = new Float64Array()\n", - "forEach": "function logger( v, i ) { console.log( '%s: %d', i, v ); };\narr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n", - "forEachAsync": "\n// Basic usage:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\narr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\n\n// Limit number of concurrent invocations:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n\n// Process sequentially:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nopts = { 'series': true };\narr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n", - "forEachRight": "function logger( v, i ) { console.log( '%s: %d', i, v ); };\narr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n", - "forEachRightAsync": "\n// Basic usage:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\narr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\n\n// Limit number of concurrent invocations:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nopts = { 'limit': 2 };\narr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n\n// Process sequentially:\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n};\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n};\nopts = { 'series': true };\narr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n", - "forIn": "function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nobj = new Foo();\nforIn( obj, logger )\n", - "forOwn": "function logger( v, k ) { console.log( '%s: %d', k, v ); };\nobj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n", - "FOURTH_PI": "FOURTH_PI\n", - "FOURTH_ROOT_EPS": "FOURTH_ROOT_EPS\n", - "FRB_SF_WAGE_RIGIDITY": "data = FRB_SF_WAGE_RIGIDITY()\n", - "fromCodePoint": "out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n", - "functionName": "v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n", - "functionSequence": "function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nf = functionSequence( a, b, c );\nz = f( 6 )\n", - "functionSequenceAsync": "function a( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, 2*x );\n }\n};\nfunction b( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x+3 );\n }\n};\nfunction c( x, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, x/5 );\n }\n};\nf = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nf( 6, done )\n", - "GAMMA_LANCZOS_G": "GAMMA_LANCZOS_G\n", - "getegid": "gid = getegid()\n", - "geteuid": "uid = geteuid()\n", - "getgid": "gid = getgid()\n", - "getGlobal": "g = getGlobal()\n", - "getPrototypeOf": "proto = getPrototypeOf( {} )\n", - "getuid": "uid = getuid()\n", - "GLAISHER": "GLAISHER\n", - "group": "collection = [ 'beep', 'boop', 'foo', 'bar' ];\ngroups = [ 'b', 'b', 'f', 'b' ];\nout = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\n\n// Output group results as indices:\ngroups = [ 'b', 'b', 'f', 'b' ];\nopts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\n\n// Output group results as index-element pairs:\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n", - "groupBy": "function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\ncollection = [ 'beep', 'boop', 'foo', 'bar' ];\nout = groupBy( collection, indicator )\n\n// Output group results as indices:\nopts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n", - "groupByAsync": "\n// Basic usage:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\narr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\n\n// Output group results as indices:\nopts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\n\n// Output group results as index-value pairs:\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\n\n// Limit number of concurrent invocations:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n\n// Process sequentially:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nopts = { 'series': true };\narr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n", - "groupIn": "function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nobj = new Foo();\nout = groupIn( obj, indicator )\n\n// Output group results as keys:\nopts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n", - "groupOwn": "function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n};\nobj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nout = groupOwn( obj, indicator )\n\n// Output group results as keys:\nopts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\n\n// Output group results as key-value pairs:\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n", - "HALF_LN2": "HALF_LN2\n", - "HALF_PI": "HALF_PI\n", - "HARRISON_BOSTON_HOUSE_PRICES": "data = HARRISON_BOSTON_HOUSE_PRICES()\n", - "HARRISON_BOSTON_HOUSE_PRICES_CORRECTED": "data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n", - "hasArrayBufferSupport": "bool = hasArrayBufferSupport()\n", - "hasAsyncAwaitSupport": "bool = hasAsyncAwaitSupport()\n", - "hasAsyncIteratorSymbolSupport": "bool = hasAsyncIteratorSymbolSupport()\n", - "hasClassSupport": "bool = hasClassSupport()\n", - "hasDefinePropertiesSupport": "bool = hasDefinePropertiesSupport()\n", - "hasDefinePropertySupport": "bool = hasDefinePropertySupport()\n", - "hasFloat32ArraySupport": "bool = hasFloat32ArraySupport()\n", - "hasFloat64ArraySupport": "bool = hasFloat64ArraySupport()\n", - "hasFunctionNameSupport": "bool = hasFunctionNameSupport()\n", - "hasGeneratorSupport": "bool = hasGeneratorSupport()\n", - "hasInt8ArraySupport": "bool = hasInt8ArraySupport()\n", - "hasInt16ArraySupport": "bool = hasInt16ArraySupport()\n", - "hasInt32ArraySupport": "bool = hasInt32ArraySupport()\n", - "hasIteratorSymbolSupport": "bool = hasIteratorSymbolSupport()\n", - "hasMapSupport": "bool = hasMapSupport()\n", - "hasNodeBufferSupport": "bool = hasNodeBufferSupport()\n", - "hasOwnProp": "beep = { 'boop': true };\nbool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n", - "hasProp": "beep = { 'boop': true };\nbool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n", - "hasProxySupport": "bool = hasProxySupport()\n", - "hasSetSupport": "bool = hasSetSupport()\n", - "hasSharedArrayBufferSupport": "bool = hasSharedArrayBufferSupport()\n", - "hasSymbolSupport": "bool = hasSymbolSupport()\n", - "hasToStringTagSupport": "bool = hasToStringTagSupport()\n", - "hasUint8ArraySupport": "bool = hasUint8ArraySupport()\n", - "hasUint8ClampedArraySupport": "bool = hasUint8ClampedArraySupport()\n", - "hasUint16ArraySupport": "bool = hasUint16ArraySupport()\n", - "hasUint32ArraySupport": "bool = hasUint32ArraySupport()\n", - "hasWeakMapSupport": "bool = hasWeakMapSupport()\n", - "hasWeakSetSupport": "bool = hasWeakSetSupport()\n", - "hasWebAssemblySupport": "bool = hasWebAssemblySupport()\n", - "HERNDON_VENUS_SEMIDIAMETERS": "d = HERNDON_VENUS_SEMIDIAMETERS()\n", - "homedir": "home = homedir()\n", - "HOURS_IN_DAY": "days = 3.14;\nhrs = days * HOURS_IN_DAY\n", - "HOURS_IN_WEEK": "wks = 3.14;\nhrs = wks * HOURS_IN_WEEK\n", - "hoursInMonth": "num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n", - "hoursInYear": "num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n", - "httpServer": "\n// Basic usage:\ncreateServer = httpServer()\n\n// Provide a request callback:\nfunction onRequest( request, response ) {\n console.log( request.url );\n response.end( 'OK' );\n};\ncreateServer = httpServer( onRequest )\n\n// Specify a specific port:\nopts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n", - "identity": "v = identity( 3.14 )\n", - "ifelse": "z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n", - "ifelseAsync": "function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nifelseAsync( predicate, 'beep', 'boop', done )\n", - "ifthen": "function x() { return 1.0; };\nfunction y() { return -1.0; };\nz = ifthen( true, x, y )\nz = ifthen( false, x, y )\n", - "ifthenAsync": "function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n};\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n};\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nifthenAsync( predicate, x, y, done )\n", - "imag": "z = new Complex128( 5.0, 3.0 );\nim = imag( z )\n", - "IMG_ACANTHUS_MOLLIS": "img = IMG_ACANTHUS_MOLLIS()\n", - "IMG_AIRPLANE_FROM_ABOVE": "img = IMG_AIRPLANE_FROM_ABOVE()\n", - "IMG_ALLIUM_OREOPHILUM": "img = IMG_ALLIUM_OREOPHILUM()\n", - "IMG_BLACK_CANYON": "img = IMG_BLACK_CANYON()\n", - "IMG_DUST_BOWL_HOME": "img = IMG_DUST_BOWL_HOME()\n", - "IMG_FRENCH_ALPINE_LANDSCAPE": "img = IMG_FRENCH_ALPINE_LANDSCAPE()\n", - "IMG_LOCOMOTION_HOUSE_CAT": "img = IMG_LOCOMOTION_HOUSE_CAT()\n", - "IMG_LOCOMOTION_NUDE_MALE": "img = IMG_LOCOMOTION_NUDE_MALE()\n", - "IMG_MARCH_PASTORAL": "img = IMG_MARCH_PASTORAL()\n", - "IMG_NAGASAKI_BOATS": "img = IMG_NAGASAKI_BOATS()\n", - "incrapcorr": "accumulator = incrapcorr();\nar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n", - "incrcount": "accumulator = incrcount();\nv = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n", - "incrcovariance": "accumulator = incrcovariance();\nv = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n", - "incrcovmat": "accumulator = incrcovmat( 2 );\nout = accumulator()\nvec = ndarray( 'float64', 1 );\nbuf = new Float64Array( 2 );\nshape = [ 2 ];\nstrides = [ 1 ];\nv = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n", - "incrcv": "accumulator = incrcv();\ncv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n", - "increwmean": "accumulator = increwmean( 0.5 );\nv = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n", - "increwstdev": "accumulator = increwstdev( 0.5 );\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n", - "increwvariance": "accumulator = increwvariance( 0.5 );\nv = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n", - "incrgmean": "accumulator = incrgmean();\nv = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n", - "incrgrubbs": "acc = incrgrubbs();\nres = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n};\nres.print()\n", - "incrhmean": "accumulator = incrhmean();\nv = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n", - "incrkmeans": "accumulator = incrkmeans( 5, 2 );\nvec = ndarray( 'float64', 1 );\nbuf = new Float64Array( 2 );\nshape = [ 2 ];\nstrides = [ 1 ];\nv = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n", - "incrkurtosis": "accumulator = incrkurtosis();\nv = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n", - "incrmaape": "accumulator = incrmaape();\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n", - "incrmae": "accumulator = incrmae();\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n", - "incrmapcorr": "accumulator = incrmapcorr( 3 );\nar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n", - "incrmape": "accumulator = incrmape();\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n", - "incrmax": "accumulator = incrmax();\nm = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n", - "incrmaxabs": "accumulator = incrmaxabs();\nm = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n", - "incrmcovariance": "accumulator = incrmcovariance( 3 );\nv = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n", - "incrmcv": "accumulator = incrmcv( 3 );\ncv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n", - "incrmda": "accumulator = incrmda();\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n", - "incrme": "accumulator = incrme();\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n", - "incrmean": "accumulator = incrmean();\nmu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n", - "incrmeanabs": "accumulator = incrmeanabs();\nmu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n", - "incrmeanabs2": "accumulator = incrmeanabs2();\nmu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n", - "incrmeanstdev": "accumulator = incrmeanstdev();\nms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n", - "incrmeanvar": "accumulator = incrmeanvar();\nmv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n", - "incrmgmean": "accumulator = incrmgmean( 3 );\nv = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n", - "incrmgrubbs": "acc = incrmgrubbs( 20 );\nres = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n};\nres.print()\n", - "incrmhmean": "accumulator = incrmhmean( 3 );\nv = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n", - "incrmidrange": "accumulator = incrmidrange();\nv = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n", - "incrmin": "accumulator = incrmin();\nm = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n", - "incrminabs": "accumulator = incrminabs();\nm = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n", - "incrminmax": "accumulator = incrminmax();\nmm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n", - "incrminmaxabs": "accumulator = incrminmaxabs();\nmm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n", - "incrmmaape": "accumulator = incrmmaape( 3 );\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n", - "incrmmae": "accumulator = incrmmae( 3 );\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n", - "incrmmape": "accumulator = incrmmape( 3 );\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n", - "incrmmax": "accumulator = incrmmax( 3 );\nm = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n", - "incrmmaxabs": "accumulator = incrmmaxabs( 3 );\nm = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n", - "incrmmda": "accumulator = incrmmda( 3 );\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n", - "incrmme": "accumulator = incrmme( 3 );\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n", - "incrmmean": "accumulator = incrmmean( 3 );\nmu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n", - "incrmmeanabs": "accumulator = incrmmeanabs( 3 );\nmu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n", - "incrmmeanabs2": "accumulator = incrmmeanabs2( 3 );\nm = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n", - "incrmmeanstdev": "accumulator = incrmmeanstdev( 3 );\nv = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n", - "incrmmeanvar": "accumulator = incrmmeanvar( 3 );\nv = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n", - "incrmmidrange": "accumulator = incrmmidrange( 3 );\nmr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n", - "incrmmin": "accumulator = incrmmin( 3 );\nm = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n", - "incrmminabs": "accumulator = incrmminabs( 3 );\nm = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n", - "incrmminmax": "accumulator = incrmminmax( 3 );\nmm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n", - "incrmminmaxabs": "accumulator = incrmminmaxabs( 3 );\nmm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n", - "incrmmpe": "accumulator = incrmmpe( 3 );\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n", - "incrmmse": "accumulator = incrmmse( 3 );\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n", - "incrmpcorr": "accumulator = incrmpcorr( 3 );\nr = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n", - "incrmpcorr2": "accumulator = incrmpcorr2( 3 );\nr2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n", - "incrmpcorrdist": "accumulator = incrmpcorrdist( 3 );\nd = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n", - "incrmpe": "accumulator = incrmpe();\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n", - "incrmprod": "accumulator = incrmprod( 3 );\np = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n", - "incrmrange": "accumulator = incrmrange( 3 );\nr = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n", - "incrmrmse": "accumulator = incrmrmse( 3 );\nr = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n", - "incrmrss": "accumulator = incrmrss( 3 );\nr = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n", - "incrmse": "accumulator = incrmse();\nm = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n", - "incrmstdev": "accumulator = incrmstdev( 3 );\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n", - "incrmsum": "accumulator = incrmsum( 3 );\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n", - "incrmsumabs": "accumulator = incrmsumabs( 3 );\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n", - "incrmsumabs2": "accumulator = incrmsumabs2( 3 );\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n", - "incrmsummary": "accumulator = incrmsummary( 3 );\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n", - "incrmsumprod": "accumulator = incrmsumprod( 3 );\ns = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n", - "incrmvariance": "accumulator = incrmvariance( 3 );\ns2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n", - "incrmvmr": "accumulator = incrmvmr( 3 );\nF = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n", - "incrpcorr": "accumulator = incrpcorr();\nr = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n", - "incrpcorr2": "accumulator = incrpcorr2();\nr2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n", - "incrpcorrdist": "accumulator = incrpcorrdist();\nd = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n", - "incrpcorrdistmat": "accumulator = incrpcorrdistmat( 2 );\nout = accumulator()\nvec = ndarray( 'float64', 1 );\nbuf = new Float64Array( 2 );\nshape = [ 2 ];\nstrides = [ 1 ];\nv = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n", - "incrpcorrmat": "accumulator = incrpcorrmat( 2 );\nout = accumulator()\nvec = ndarray( 'float64', 1 );\nbuf = new Float64Array( 2 );\nshape = [ 2 ];\nstrides = [ 1 ];\nv = vec( buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n", - "incrprod": "accumulator = incrprod();\nv = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n", - "incrrange": "accumulator = incrrange();\nv = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n", - "incrrmse": "accumulator = incrrmse();\nr = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n", - "incrrss": "accumulator = incrrss();\nr = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n", - "incrskewness": "accumulator = incrskewness();\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n", - "incrspace": "arr = incrspace( 0, 11, 2 )\n", - "incrstdev": "accumulator = incrstdev();\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n", - "incrsum": "accumulator = incrsum();\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n", - "incrsumabs": "accumulator = incrsumabs();\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n", - "incrsumabs2": "accumulator = incrsumabs2();\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n", - "incrsummary": "accumulator = incrsummary();\ns = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n", - "incrsumprod": "accumulator = incrsumprod();\ns = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n", - "incrvariance": "accumulator = incrvariance();\ns2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n", - "incrvmr": "accumulator = incrvmr();\nD = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n", - "incrwmean": "accumulator = incrwmean();\nmu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n", - "ind2sub": "d = [ 3, 3, 3 ];\ns = ind2sub( d, 17 )\n\n// Provide an output array:\nout = new Array( d.length );\ns = ind2sub( out, d, 17 )\nbool = ( s === out )\n", - "indexOf": "\n// Basic usage:\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\n\n// Using a `fromIndex`:\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\n\n// `fromIndex` which exceeds `array` length:\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\n\n// Negative `fromIndex`:\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\n\n// Negative `fromIndex` exceeding input `array` length:\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\n\n// Array-like objects:\nstr = 'bebop';\nidx = indexOf( str, 'o' )\n", - "inherit": "\n// Create a parent constructor:\nfunction Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\n\n// Create a child constructor:\nfunction Bar() { Foo.call( this ); return this; };\n\n// Setup inheritance:\ninherit( Bar, Foo );\nbar = new Bar();\nv = bar.beep()\n", - "inheritedEnumerableProperties": "props = inheritedEnumerableProperties( {} )\n", - "inheritedEnumerablePropertySymbols": "symbols = inheritedEnumerablePropertySymbols( [] )\n", - "inheritedKeys": "keys = inheritedKeys( {} )\n", - "inheritedNonEnumerableProperties": "props = inheritedNonEnumerableProperties( {} )\n", - "inheritedNonEnumerablePropertyNames": "keys = inheritedNonEnumerablePropertyNames( {} )\n", - "inheritedNonEnumerablePropertySymbols": "symbols = inheritedNonEnumerablePropertySymbols( [] )\n", - "inheritedProperties": "symbols = inheritedProperties( [] )\n", - "inheritedPropertyDescriptor": "desc = inheritedPropertyDescriptor( {}, 'toString' )\n", - "inheritedPropertyDescriptors": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\ndesc = inheritedPropertyDescriptors( obj )\n", - "inheritedPropertyNames": "keys = inheritedPropertyNames( [] )\n", - "inheritedPropertySymbols": "symbols = inheritedPropertySymbols( [] )\n", - "inheritedWritableProperties": "props = inheritedWritableProperties( {} )\n", - "inheritedWritablePropertyNames": "keys = inheritedWritablePropertyNames( {} )\n", - "inheritedWritablePropertySymbols": "symbols = inheritedWritablePropertySymbols( [] )\n", - "inmap": "function foo( v, i ) { return v * i; };\narr = [ 1.0, 2.0, 3.0 ];\nout = inmap( arr, foo )\nbool = ( out === arr )\n", - "inmapAsync": "\n// Basic usage:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\narr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n\n// Process sequentially:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nopts = { 'series': true };\narr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n", - "inmapRight": "function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\narr = [ 1.0, 2.0, 3.0 ];\nout = inmapRight( arr, foo )\nbool = ( out === arr )\n", - "inmapRightAsync": "\n// Basic usage:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\narr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nopts = { 'limit': 2 };\narr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n\n// Process sequentially:\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n};\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n};\nopts = { 'series': true };\narr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n", - "inspectSinkStream": "function clbk( chunk, idx ) { console.log( chunk.toString() ); };\ns = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n", - "inspectStream": "function clbk( chunk, idx ) { console.log( chunk.toString() ); };\ns = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n", - "instanceOf": "bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n", - "INT8_MAX": "INT8_MAX\n", - "INT8_MIN": "INT8_MIN\n", - "INT8_NUM_BYTES": "INT8_NUM_BYTES\n", - "Int8Array": "arr = new Int8Array()\n", - "INT16_MAX": "INT16_MAX\n", - "INT16_MIN": "INT16_MIN\n", - "INT16_NUM_BYTES": "INT16_NUM_BYTES\n", - "Int16Array": "arr = new Int16Array()\n", - "INT32_MAX": "INT32_MAX\n", - "INT32_MIN": "INT32_MIN\n", - "INT32_NUM_BYTES": "INT32_NUM_BYTES\n", - "Int32Array": "arr = new Int32Array()\n", - "IS_BIG_ENDIAN": "IS_BIG_ENDIAN\n", - "IS_BROWSER": "IS_BROWSER\n", - "IS_DARWIN": "IS_DARWIN\n", - "IS_ELECTRON": "IS_ELECTRON\n", - "IS_ELECTRON_MAIN": "IS_ELECTRON_MAIN\n", - "IS_ELECTRON_RENDERER": "IS_ELECTRON_RENDERER\n", - "IS_LITTLE_ENDIAN": "IS_LITTLE_ENDIAN\n", - "IS_NODE": "IS_NODE\n", - "IS_WEB_WORKER": "IS_WEB_WORKER\n", - "IS_WINDOWS": "IS_WINDOWS\n", - "isAbsolutePath": "\n// Windows environment:\nbool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n\n// POSIX environment:\nbool = isAbsolutePath( '/foo/bar/baz' )\n", - "isAccessorProperty": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nbool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n", - "isAccessorPropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nbool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n", - "isAlphagram": "out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n", - "isAlphaNumeric": "bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n", - "isAnagram": "str1 = 'I am a weakish speller';\nstr2 = 'William Shakespeare';\nbool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n", - "isArguments": "function foo() { return arguments; };\nbool = isArguments( foo() )\nbool = isArguments( [] )\n", - "isArray": "bool = isArray( [] )\nbool = isArray( {} )\n", - "isArrayArray": "bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n", - "isArrayBuffer": "bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n", - "isArrayLength": "bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n", - "isArrayLike": "bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n", - "isArrayLikeObject": "bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n", - "isASCII": "str = 'beep boop';\nbool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n", - "isBetween": "bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n", - "isBetweenArray": "arr = [ 3.0, 3.14, 4.0 ];\nbool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n", - "isBinaryString": "bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n", - "isBoolean": "bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n", - "isBooleanArray": "bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n", - "isBoxedPrimitive": "bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n", - "isBuffer": "bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n", - "isCapitalized": "bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n", - "isCentrosymmetricMatrix": "mat = ndarray( 'generic', 2 );\nM = mat( [ 2, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nbool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n", - "isCircular": "obj = { 'beep': 'boop' };\nobj.self = obj;\nbool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n", - "isCircularArray": "arr = [ 1, 2, 3 ];\narr.push( arr );\nbool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n", - "isCircularPlainObject": "obj = { 'beep': 'boop' };\nobj.self = obj;\nbool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n", - "isCollection": "bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n", - "isComplex": "bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n", - "isComplex64": "bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n", - "isComplex64Array": "bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n", - "isComplex128": "bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n", - "isComplex128Array": "bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n", - "isComplexLike": "bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n", - "isComplexTypedArray": "bool = isComplexTypedArray( new Complex64Array( 10 ) )\n", - "isConfigurableProperty": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nbool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n", - "isConfigurablePropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nbool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n", - "isDataProperty": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nbool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n", - "isDataPropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nbool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n", - "isDateObject": "bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n", - "isDigitString": "bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n", - "isEmailAddress": "bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n", - "isEmptyArray": "bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n", - "isEmptyObject": "bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n", - "isEmptyString": "bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n", - "isEnumerableProperty": "beep = { 'boop': true };\nbool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n", - "isEnumerablePropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nbool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n", - "isError": "bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n", - "isEvalError": "bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n", - "isEven": "bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n", - "isFalsy": "bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n", - "isFalsyArray": "bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n", - "isFinite": "bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n", - "isFiniteArray": "bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n", - "isFloat32Array": "bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n", - "isFloat64Array": "bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n", - "isFunction": "function beep() {};\nbool = isFunction( beep )\nbool = isFunction( {} )\n", - "isFunctionArray": "function beep() {};\nfunction boop() {};\nbool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n", - "isGeneratorObject": "function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n};\nbool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n", - "isGeneratorObjectLike": "obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n};\nbool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n", - "isHexString": "bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n", - "isInfinite": "bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n", - "isInheritedProperty": "beep = { 'boop': true };\nbool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n", - "isInt8Array": "bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n", - "isInt16Array": "bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n", - "isInt32Array": "bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n", - "isInteger": "bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n", - "isIntegerArray": "bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n", - "isIterableLike": "bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n", - "isIteratorLike": "obj = {\n 'next': function noop() {}\n};\nbool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n", - "isJSON": "bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n", - "isLeapYear": "bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n", - "isLowercase": "bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n", - "isMatrixLike": "M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nbool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n", - "isMethod": "beep = { 'boop': function beep() { return 'beep'; } };\nbool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n", - "isMethodIn": "beep = { 'boop': true };\nbool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n", - "isNamedTypedTupleLike": "Point = namedtypedtuple( [ 'x', 'y' ] );\np = new Point();\nbool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n", - "isnan": "bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n", - "isNaNArray": "bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n", - "isNativeFunction": "bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n", - "isndarrayLike": "M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nbool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n", - "isNegativeInteger": "bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n", - "isNegativeIntegerArray": "bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n", - "isNegativeNumber": "bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n", - "isNegativeNumberArray": "bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n", - "isNegativeZero": "bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n", - "isNodeBuiltin": "bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n", - "isNodeDuplexStreamLike": "Stream = require( 'stream' ).Duplex;\ns = new Stream();\nbool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n", - "isNodeReadableStreamLike": "Stream = require( 'stream' ).Readable;\ns = new Stream();\nbool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n", - "isNodeREPL": "bool = isNodeREPL()\n", - "isNodeStreamLike": "Stream = require( 'stream' ).Stream;\ns = new Stream();\nbool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n", - "isNodeTransformStreamLike": "Stream = require( 'stream' ).Transform;\ns = new Stream();\nbool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n", - "isNodeWritableStreamLike": "Stream = require( 'stream' ).Writable;\ns = new Stream();\nbool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n", - "isNonConfigurableProperty": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nbool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n", - "isNonConfigurablePropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nbool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n", - "isNonEnumerableProperty": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nbool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n", - "isNonEnumerablePropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nbool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n", - "isNonNegativeInteger": "bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n", - "isNonNegativeIntegerArray": "bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n", - "isNonNegativeNumber": "bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n", - "isNonNegativeNumberArray": "bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n", - "isNonPositiveInteger": "bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n", - "isNonPositiveIntegerArray": "bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n", - "isNonPositiveNumber": "bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n", - "isNonPositiveNumberArray": "bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n", - "isNonSymmetricMatrix": "mat = ndarray( 'generic', 2 );\nM = mat( [ 1, 2, 3, 4 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nbool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n", - "isNull": "bool = isNull( null )\nbool = isNull( true )\n", - "isNullArray": "bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n", - "isNumber": "bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n", - "isNumberArray": "bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n", - "isNumericArray": "bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n", - "isObject": "bool = isObject( {} )\nbool = isObject( true )\n", - "isObjectArray": "bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n", - "isObjectLike": "bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n", - "isOdd": "bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n", - "isoWeeksInYear": "num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n", - "isPersymmetricMatrix": "mat = ndarray( 'generic', 2 );\nM = mat( [ 1, 2, 3, 1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nbool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n", - "isPlainObject": "bool = isPlainObject( {} )\nbool = isPlainObject( null )\n", - "isPlainObjectArray": "bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n", - "isPositiveInteger": "bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n", - "isPositiveIntegerArray": "bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n", - "isPositiveNumber": "bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n", - "isPositiveNumberArray": "bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n", - "isPositiveZero": "bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n", - "isPrimitive": "bool = isPrimitive( true )\nbool = isPrimitive( {} )\n", - "isPrimitiveArray": "bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n", - "isPRNGLike": "bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n", - "isProbability": "bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n", - "isProbabilityArray": "bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n", - "isPrototypeOf": "function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nbar = new Bar();\nbool = isPrototypeOf( bar, Foo.prototype )\n", - "isRangeError": "bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n", - "isReadableProperty": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nbool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n", - "isReadablePropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nbool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n", - "isReadOnlyProperty": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nbool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n", - "isReadOnlyPropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nbool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n", - "isReadWriteProperty": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nbool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n", - "isReadWritePropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nbool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n", - "isReferenceError": "bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n", - "isRegExp": "bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n", - "isRegExpString": "bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n", - "isRelativePath": "\n// Windows environments:\nbool = isRelativePath( 'foo\\\\bar\\\\baz' )\n\n// POSIX environments:\nbool = isRelativePath( './foo/bar/baz' )\n", - "isSafeInteger": "bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n", - "isSafeIntegerArray": "arr = [ -3.0, new Number(0.0), 2.0 ];\nbool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n", - "isSameValue": "bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n", - "isSameValueZero": "bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n", - "isSharedArrayBuffer": "\n// Assuming an environment supports SharedArrayBuffer...\nbool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n", - "isSkewCentrosymmetricMatrix": "mat = ndarray( 'generic', 2 );\nM = mat( [ 2, 1, -1, -2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nbool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n", - "isSkewPersymmetricMatrix": "mat = ndarray( 'generic', 2 );\nM = mat( [ 1, 0, 0, -1 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nbool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n", - "isSkewSymmetricMatrix": "mat = ndarray( 'generic', 2 );\nM = mat( [ 0, -1, 1, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nbool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n", - "isSquareMatrix": "mat = ndarray( 'generic', 2 );\nM = mat( [ 0, 0, 0, 0 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nbool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n", - "isStrictEqual": "bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n", - "isString": "bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n", - "isStringArray": "bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n", - "isSymbol": "bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n", - "isSymbolArray": "bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n", - "isSymmetricMatrix": "mat = ndarray( 'generic', 2 );\nM = mat( [ 0, 1, 1, 2 ], [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nbool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n", - "isSyntaxError": "bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n", - "isTruthy": "bool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n", - "isTruthyArray": "bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n", - "isTypedArray": "bool = isTypedArray( new Int8Array( 10 ) )\n", - "isTypedArrayLength": "bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n", - "isTypedArrayLike": "bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n 'length': 10,\n 'byteOffset': 0,\n 'byteLength': 10,\n 'BYTES_PER_ELEMENT': 4\n})\n", - "isTypeError": "bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n", - "isUint8Array": "bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n", - "isUint8ClampedArray": "bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n", - "isUint16Array": "bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n", - "isUint32Array": "bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n", - "isUNCPath": "bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n", - "isUndefined": "bool = isUndefined( void 0 )\nbool = isUndefined( null )\n", - "isUndefinedOrNull": "bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n", - "isUnityProbabilityArray": "bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n", - "isUppercase": "bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n", - "isURI": "bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n\n// No scheme:\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\n\n// Illegal characters:\nbool = isURI( 'http://' )\n\n// Invalid path:\nbool = isURI( 'http:////foo.html' )\n\n// Incomplete hex escapes:\nbool = isURI( 'http://example.w3.org/%a' )\n", - "isURIError": "bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n", - "isVectorLike": "M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nbool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n", - "isWhitespace": "bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n", - "isWritableProperty": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nbool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n", - "isWritablePropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nbool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n", - "isWriteOnlyProperty": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nbool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n", - "isWriteOnlyPropertyIn": "obj = { 'boop': true };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nbool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n", - "iterAdd": "it1 = array2iterator( [ 1.0, 2.0 ] );\nit2 = array2iterator( [ 3.0, 4.0 ] );\nit = iterAdd( it1, it2 );\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n", - "iterAdvance": "arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nit = iterAdvance( arr, 4 );\nv = it.next().value\nbool = it.next().done\n", - "iterAny": "arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nbool = iterAny( arr )\n", - "iterAnyBy": "arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nbool = iterAnyBy( arr, fcn )\n", - "iterator2array": "opts = { 'iter': 10 };\narr = iterator2array( random.iterators.randu( opts ) )\n", - "iterator2arrayview": "it = random.iterators.randu({ 'iter': 10 });\nout = new Float64Array( 20 );\narr = iterator2arrayview( it, out, 5, 15 )\n", - "iterator2arrayviewRight": "it = random.iterators.randu({ 'iter': 10 });\nout = new Float64Array( 20 );\narr = iterator2arrayviewRight( it, out, 5, 15 )\n", - "iteratorStream": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\nit = random.iterators.randu( opts );\ns = iteratorStream( it );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "IteratorSymbol": "s = IteratorSymbol\n", - "iterawgn": "src = iterSineWave();\nit = iterawgn( src, 0.5 );\nv = it.next().value\nv = it.next().value\n", - "iterawln": "src = iterSineWave();\nit = iterawln( src, 0.5 );\nv = it.next().value\nv = it.next().value\n", - "iterawun": "src = iterSineWave();\nit = iterawun( src, 0.5 );\nv = it.next().value\nv = it.next().value\n", - "iterBartlettHannPulse": "it = iterBartlettHannPulse();\nv = it.next().value\nv = it.next().value\n", - "iterBartlettPulse": "it = iterBartlettPulse();\nv = it.next().value\nv = it.next().value\n", - "iterConcat": "it1 = array2iterator( [ 1, 2 ] );\nit2 = array2iterator( [ 3, 4 ] );\nit = iterConcat( it1, it2 );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n", - "iterConstant": "it = iterConstant( 3.14 );\nv = it.next().value\nv = it.next().value\n", - "iterCosineWave": "it = iterCosineWave();\nv = it.next().value\nv = it.next().value\n", - "iterCounter": "it = iterCounter( random.iterators.randu() );\nv = it.next().value\nv = it.next().value\n", - "itercugmean": "arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nit = itercugmean( arr );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n", - "itercuhmean": "arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nit = itercuhmean( arr );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n", - "itercumax": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercumax( arr );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itercumaxabs": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercumaxabs( arr );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itercumean": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercumean( arr );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itercumeanabs": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercumeanabs( arr );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itercumeanabs2": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercumeanabs2( arr );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itercumidrange": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercumidrange( arr );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n", - "itercumin": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercumin( arr );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itercuminabs": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercuminabs( arr );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itercuprod": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercuprod( arr );\np = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n", - "itercurange": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercurange( arr );\nr = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n", - "itercusum": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercusum( arr );\ns = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n", - "itercusumabs": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercusumabs( arr );\ns = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n", - "itercusumabs2": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itercusumabs2( arr );\ns = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n", - "iterDedupe": "arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nit = iterDedupe( arr );\nv = it.next().value\nv = it.next().value\nv = it.next().value\n", - "iterDedupeBy": "arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nit = iterDedupeBy( arr, fcn );\nv = it.next().value\nv = it.next().value\nv = it.next().value\n", - "iterDiracComb": "it = iterDiracComb();\nv = it.next().value\nv = it.next().value\n", - "iterDivide": "it1 = array2iterator( [ 3.0, 2.0 ] );\nit2 = array2iterator( [ 1.0, 4.0 ] );\nit = iterDivide( it1, it2 );\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n", - "iterEmpty": "it = iterEmpty();\nbool = it.next().done\n", - "iterEvery": "arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nbool = iterEvery( arr )\n", - "iterEveryBy": "arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nbool = iterEveryBy( arr, fcn )\n", - "iterFibonacci": "it = iterFibonacci();\nv = it.next().value\nv = it.next().value\n", - "iterFill": "it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nr = it.next().value\nr = it.next().value\nr = it.next().value\n", - "iterFilter": "function f( v ) { return ( v > 2 ); };\nit1 = array2iterator( [ 1, 3, 2, 4 ] );\nit2 = iterFilter( it1, f );\nv = it2.next().value\nv = it2.next().value\n", - "iterFilterMap": "function f( v ) { if ( v > 2 ) { return v * 10 }; };\nit1 = array2iterator( [ 1, 3, 2, 4 ] );\nit2 = iterFilterMap( it1, f );\nv = it2.next().value\nv = it2.next().value\n", - "iterFirst": "arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nv = iterFirst( arr )\n", - "iterFlatTopPulse": "it = iterFlatTopPulse();\nv = it.next().value\nv = it.next().value\n", - "iterFlow": "o = {};\no.head = iterHead;\no.some = iterSome;\nfiter = iterFlow( o )\n", - "iterForEach": "function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nit = iterForEach( random.iterators.randu(), f );\nr = it.next().value\nr = it.next().value\n", - "iterHannPulse": "it = iterHannPulse();\nv = it.next().value\nv = it.next().value\n", - "iterHead": "it = iterHead( random.iterators.randu(), 5 );\nr = it.next().value\nr = it.next().value\n", - "iterIntersection": "it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nit2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nit = iterIntersection( it1, it2 );\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n", - "iterIntersectionByHash": "it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nit2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nit = iterIntersectionByHash( it1, it2, f );\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n", - "iterLanczosPulse": "it = iterLanczosPulse();\nv = it.next().value\nv = it.next().value\n", - "iterLast": "arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nv = iterLast( arr )\n", - "iterLength": "arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nlen = iterLength( arr )\n", - "iterMap": "function f( v ) { return v * 10.0; };\nit = iterMap( random.iterators.randu(), f );\nr = it.next().value\nr = it.next().value\n", - "iterMapN": "it1 = array2iterator( [ 1.0, 2.0 ] );\nit2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nit = iterMapN( it1, it2, fcn );\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n", - "itermax": "arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nm = itermax( arr )\n", - "itermaxabs": "arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nm = itermaxabs( arr )\n", - "itermean": "arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = itermean( arr )\n", - "itermeanabs": "arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nm = itermeanabs( arr )\n", - "itermeanabs2": "arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nm = itermeanabs2( arr )\n", - "itermidrange": "arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nv = itermidrange( arr )\n", - "itermin": "arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nm = itermin( arr )\n", - "iterminabs": "arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nm = iterminabs( arr )\n", - "itermmax": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermmax( arr, 3 );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itermmaxabs": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermmaxabs( arr, 3 );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itermmean": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermmean( arr, 3 );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itermmeanabs": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermmeanabs( arr, 3 );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itermmeanabs2": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermmeanabs2( arr, 3 );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itermmidrange": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermmidrange( arr, 3 );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n", - "itermmin": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermmin( arr, 3 );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itermminabs": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermminabs( arr, 3 );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "iterMod": "it1 = array2iterator( [ 3.0, 2.0 ] );\nit2 = array2iterator( [ 1.0, 4.0 ] );\nit = iterMod( it1, it2 );\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n", - "itermprod": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermprod( arr, 3 );\np = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n", - "itermrange": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermrange( arr, 3 );\nm = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n", - "itermsum": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermsum( arr, 3 );\ns = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n", - "itermsumabs": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermsumabs( arr, 3 );\ns = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n", - "itermsumabs2": "arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nit = itermsumabs2( arr, 3 );\ns = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n", - "iterMultiply": "it1 = array2iterator( [ 1.0, 2.0 ] );\nit2 = array2iterator( [ 3.0, 4.0 ] );\nit = iterMultiply( it1, it2 );\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n", - "iterNone": "arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nbool = iterNone( arr )\n", - "iterNoneBy": "arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nbool = iterNoneBy( arr, fcn )\n", - "iterNonFibonacci": "it = iterNonFibonacci();\nv = it.next().value\nv = it.next().value\n", - "iterNth": "arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nv = iterNth( arr, 3 )\n", - "iterPeriodicSinc": "it = iterPeriodicSinc( 7 );\nv = it.next().value\nv = it.next().value\n", - "iterPipeline": "it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nit2 = iterThunk( iterSomeBy, 5, f );\np = iterPipeline( it1, it2 );\nbool = p( random.iterators.randu() )\n", - "iterPop": "it1 = array2iterator( [ 1, 2 ] );\nit2 = iterPop( it1 );\nv = it2.next().value\nbool = it2.next().done\n", - "iterprod": "arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\ns = iterprod( arr )\n", - "iterPulse": "it = iterPulse();\nv = it.next().value\nv = it.next().value\n", - "iterPush": "it1 = array2iterator( [ 1, 2 ] );\nit2 = iterPush( it1, 3, 4 );\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nbool = it2.next().done\n", - "iterrange": "arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nv = iterrange( arr )\n", - "iterReject": "function f( v ) { return ( v > 2 ); };\nit1 = array2iterator( [ 1, 3, 2, 4 ] );\nit2 = iterReject( it1, f );\nv = it2.next().value\nv = it2.next().value\n", - "iterReplicate": "it1 = array2iterator( [ 1, 2, 3, 4 ] );\nit2 = iterReplicate( it1, 2 );\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n", - "iterReplicateBy": "it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nit2 = iterReplicateBy( it1, f );\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n", - "iterSawtoothWave": "it = iterSawtoothWave();\nv = it.next().value\nv = it.next().value\n", - "iterShift": "it1 = array2iterator( [ 1, 2 ] );\nit2 = iterShift( it1 );\nv = it2.next().value\nbool = it2.next().done\n", - "iterSineWave": "it = iterSineWave();\nv = it.next().value\nv = it.next().value\n", - "iterSlice": "it = iterSlice( random.iterators.randu(), 5, 10 );\nr = it.next().value\nr = it.next().value\n", - "iterSome": "arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nbool = iterSome( arr, 3 )\n", - "iterSomeBy": "arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nbool = iterSomeBy( arr, 3, fcn )\n", - "iterSquareWave": "it = iterSquareWave();\nv = it.next().value\nv = it.next().value\n", - "iterstdev": "arr = array2iterator( [ 2.0, -5.0 ] );\nm = iterstdev( arr )\n", - "iterSubtract": "it1 = array2iterator( [ 1.0, 5.0 ] );\nit2 = array2iterator( [ 3.0, 4.0 ] );\nit = iterSubtract( it1, it2 );\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n", - "itersum": "arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\ns = itersum( arr )\n", - "itersumabs": "arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\ns = itersumabs( arr )\n", - "itersumabs2": "arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\ns = itersumabs2( arr )\n", - "iterThunk": "fcn = iterThunk( iterSome, 3 );\narr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nbool = fcn( arr )\n", - "iterTriangleWave": "it = iterTriangleWave();\nv = it.next().value\nv = it.next().value\n", - "iterUnion": "it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nit2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nit = iterUnion( it1, it2 );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n", - "iterUnique": "it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nit2 = iterUnique( it1 );\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nbool = it2.next().done\n", - "iterUniqueBy": "it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nit2 = iterUniqueBy( it1, f );\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nbool = it2.next().done\n", - "iterUniqueByHash": "it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nit2 = iterUniqueByHash( it1, f );\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nbool = it2.next().done\n", - "iterUnshift": "it1 = array2iterator( [ 1, 2 ] );\nit2 = iterUnshift( it1, 3, 4 );\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nbool = it2.next().done\n", - "itervariance": "arr = array2iterator( [ 2.0, -5.0 ] );\ns2 = itervariance( arr )\n", - "joinStream": "s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n", - "keyBy": "function toKey( v ) { return v.a; };\narr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n", - "keyByRight": "function toKey( v ) { return v.a; };\narr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n", - "keysIn": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\nkeys = keysIn( obj )\n", - "kruskalTest": "\n// Data from Hollander & Wolfe (1973), p. 116:\nx = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\ny = [ 3.8, 2.7, 4.0, 2.4 ];\nz = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nout = kruskalTest( x, y, z )\narr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n];\ngroups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n];\nout = kruskalTest( arr, { 'groups': groups })\n", - "kstest": "\n// Verify that data is drawn from a normal distribution:\nrnorm = base.random.normal.factory({ 'seed': 4839 });\nx = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n// Test against N(0,1)\nout = kstest( x, 'normal', 0.0, 1.0 )\n\n// Test against N(3,1)\nout = kstest( x, 'normal', 3.0, 1.0 )\n\n// Verify that data is drawn from a uniform distribution:\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 })\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\n\n// Print output:\nout.print()\n\n// Set custom significance level:\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 })\n\n// Carry out one-sided hypothesis tests:\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 });\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' })\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' })\n\n// Set `sorted` option to true when data is in increasing order:\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true })\n", - "LinkedList": "list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n", - "linspace": "arr = linspace( 0, 100, 6 )\n", - "LIU_NEGATIVE_OPINION_WORDS_EN": "list = LIU_NEGATIVE_OPINION_WORDS_EN()\n", - "LIU_POSITIVE_OPINION_WORDS_EN": "list = LIU_POSITIVE_OPINION_WORDS_EN()\n", - "LN_HALF": "LN_HALF\n", - "LN_PI": "LN_PI\n", - "LN_SQRT_TWO_PI": "LN_SQRT_TWO_PI\n", - "LN_TWO_PI": "LN_TWO_PI\n", - "LN2": "LN2\n", - "LN10": "LN10\n", - "LOG2E": "LOG2E\n", - "LOG10E": "LOG10E\n", - "logspace": "arr = logspace( 0, 2, 6 )\n", - "lowercase": "out = lowercase( 'bEEp' )\n", - "lowercaseKeys": "obj = { 'A': 1, 'B': 2 };\nout = lowercaseKeys( obj )\n", - "lowess": "x = new Float64Array( 100 );\ny = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n}\nout = lowess( x, y );\nyhat = out.y;\nh = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n", - "lpad": "out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n", - "ltrim": "out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n", - "MALE_FIRST_NAMES_EN": "list = MALE_FIRST_NAMES_EN()\n", - "mapFun": "function fcn( i ) { return i; };\narr = mapFun( fcn, 5 )\n", - "mapFunAsync": "\n// Basic usage:\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n};\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n};\nmapFunAsync( fcn, 10, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n};\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n};\nopts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\n\n// Sequential invocation:\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n};\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n};\nopts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n", - "mapKeys": "function transform( key, value ) { return key + value; };\nobj = { 'a': 1, 'b': 2 };\nout = mapKeys( obj, transform )\n", - "mapKeysAsync": "\n// Basic usage:\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nobj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\n\n// Limit number of concurrent invocations:\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nopts = { 'limit': 2 };\nobj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n\n// Process sequentially:\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nopts = { 'series': true };\nobj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n", - "mapValues": "function transform( value, key ) { return key + value; };\nobj = { 'a': 1, 'b': 2 };\nout = mapValues( obj, transform )\n", - "mapValuesAsync": "\n// Basic usage:\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nobj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\n\n// Limit number of concurrent invocations:\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nopts = { 'limit': 2 };\nobj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n\n// Process sequentially:\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n};\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n};\nopts = { 'series': true };\nobj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n", - "MAX_ARRAY_LENGTH": "MAX_ARRAY_LENGTH\n", - "MAX_TYPED_ARRAY_LENGTH": "MAX_TYPED_ARRAY_LENGTH\n", - "memoize": "function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n};\nmemoized = memoize( factorial );\nv = memoized( 5 )\nv = memoized( 5 )\n", - "merge": "target = { 'a': 'beep' };\nsource = { 'a': 'boop', 'b': 'bap' };\nout = merge( target, source )\nbool = ( out === target )\n", - "MILLISECONDS_IN_DAY": "days = 3.14;\nms = days * MILLISECONDS_IN_DAY\n", - "MILLISECONDS_IN_HOUR": "hrs = 3.14;\nms = hrs * MILLISECONDS_IN_HOUR\n", - "MILLISECONDS_IN_MINUTE": "mins = 3.14;\nms = mins * MILLISECONDS_IN_MINUTE\n", - "MILLISECONDS_IN_SECOND": "secs = 3.14;\nms = secs * MILLISECONDS_IN_SECOND\n", - "MILLISECONDS_IN_WEEK": "weeks = 3.14;\nms = weeks * MILLISECONDS_IN_WEEK\n", - "MINARD_NAPOLEONS_MARCH": "data = MINARD_NAPOLEONS_MARCH();\narmy = data.army\ncities = data.cities\nlabels = data.labels\nriver = data.river\nt = data.temperature\n", - "MINUTES_IN_DAY": "days = 3.14;\nmins = days * MINUTES_IN_DAY\n", - "MINUTES_IN_HOUR": "hrs = 3.14;\nmins = hrs * MINUTES_IN_HOUR\n", - "MINUTES_IN_WEEK": "wks = 3.14;\nmins = wks * MINUTES_IN_WEEK\n", - "minutesInMonth": "num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n", - "minutesInYear": "num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n", - "MOBY_DICK": "data = MOBY_DICK()\n", - "MONTH_NAMES_EN": "list = MONTH_NAMES_EN()\n", - "MONTHS_IN_YEAR": "yrs = 3.14;\nmons = yrs * MONTHS_IN_YEAR\n", - "moveProperty": "obj1 = { 'a': 'b' };\nobj2 = {};\nbool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n", - "namedtypedtuple": "opts = {};\nopts.name = 'Point';\nfactory = namedtypedtuple( [ 'x', 'y' ], opts );\ntuple = factory();\n", - "nativeClass": "str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n", - "ndarray": "ctor = ndarray( 'generic', 2 )\n\n// To create a new instance...\nb = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nd = [ 2, 2 ]; // shape\ns = [ 2, 1 ]; // strides\no = 0; // index offset\narr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nv = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n", - "ndarrayCastingModes": "out = ndarrayCastingModes()\n", - "ndarrayDataTypes": "out = ndarrayDataTypes()\n", - "ndarrayIndexModes": "out = ndarrayIndexModes()\n", - "ndarrayMemoized": "ctor = ndarrayMemoized( 'generic', 2 )\nf = ndarrayMemoized( 'generic', 2 )\nbool = ( f === ctor )\n\n// To create a new instance...\nb = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nd = [ 2, 2 ]; // shape\ns = [ 2, 1 ]; // strides\no = 0; // index offset\narr = ctor( b, d, s, o, 'row-major' )\n\n// Get an element using subscripts:\nv = arr.get( 1, 1 )\n\n// Get an element using a linear index:\nv = arr.iget( 3 )\n\n// Set an element using subscripts:\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\n\n// Set an element using a linear index:\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n", - "ndarrayMinDataType": "dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n", - "ndarrayNextDataType": "out = ndarrayNextDataType( 'float32' )\n", - "ndarrayOrders": "out = ndarrayOrders()\n", - "ndarrayPromotionRules": "out = ndarrayPromotionRules( 'float32', 'int32' )\n", - "ndarraySafeCasts": "out = ndarraySafeCasts( 'float32' )\n", - "ndarraySameKindCasts": "out = ndarraySameKindCasts( 'float32' )\n", - "NIGHTINGALES_ROSE": "data = NIGHTINGALES_ROSE()\n", - "NINF": "NINF\n", - "NODE_VERSION": "NODE_VERSION\n", - "none": "arr = [ 0, 0, 0, 0, 0 ];\nbool = none( arr )\n", - "noneBy": "function negative( v ) { return ( v < 0 ); };\narr = [ 1, 2, 3, 4 ];\nbool = noneBy( arr, negative )\n", - "noneByAsync": "\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\narr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'series': true };\narr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n", - "noneByRight": "function positive( v ) { return ( v > 0 ); };\narr = [ -1, -2, -3, -4 ];\nbool = noneByRight( arr, positive )\n", - "noneByRightAsync": "\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\narr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'limit': 2 };\narr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'series': true };\narr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n", - "nonEnumerableProperties": "obj = {};\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nprops = nonEnumerableProperties( obj )\n", - "nonEnumerablePropertiesIn": "props = nonEnumerablePropertiesIn( [] )\n", - "nonEnumerablePropertyNames": "obj = {};\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nkeys = nonEnumerablePropertyNames( obj )\n", - "nonEnumerablePropertyNamesIn": "obj = {};\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nkeys = nonEnumerablePropertyNamesIn( obj )\n", - "nonEnumerablePropertySymbols": "obj = {};\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nsym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nsymbols = nonEnumerablePropertySymbols( obj )\n", - "nonEnumerablePropertySymbolsIn": "obj = {};\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nsym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nsymbols = nonEnumerablePropertySymbolsIn( obj )\n", - "noop": "noop();\n", - "now": "ts = now()\n", - "NUM_CPUS": "NUM_CPUS\n", - "Number": "v = new Number( 5 )\n", - "objectEntries": "obj = { 'beep': 'boop', 'foo': 'bar' };\nentries = objectEntries( obj )\n", - "objectEntriesIn": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\nentries = objectEntriesIn( obj )\n", - "objectFromEntries": "entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nobj = objectFromEntries( entries )\n", - "objectInverse": "\n// Basic usage:\nobj = { 'a': 'beep', 'b': 'boop' };\nout = objectInverse( obj )\n\n// Duplicate values:\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\n\n// Override duplicate values:\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n", - "objectInverseBy": "\n// Basic usage:\nfunction transform( key, value ) { return key + value; };\nobj = { 'a': 'beep', 'b': 'boop' };\nout = objectInverseBy( obj, transform )\n\n// Duplicate values:\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\n\n// Override duplicate values:\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n", - "objectKeys": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\nkeys = objectKeys( obj )\n", - "objectValues": "obj = { 'beep': 'boop', 'foo': 'bar' };\nvals = objectValues( obj )\n", - "objectValuesIn": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\nvalues = objectValuesIn( obj )\n", - "omit": "obj1 = { 'a': 1, 'b': 2 };\nobj2 = omit( obj1, 'b' )\n", - "omitBy": "function predicate( key, value ) { return ( value > 1 ); };\nobj1 = { 'a': 1, 'b': 2 };\nobj2 = omitBy( obj1, predicate )\n", - "openURL": "out = openURL( 'https://google.com' );\n", - "PACE_BOSTON_HOUSE_PRICES": "data = PACE_BOSTON_HOUSE_PRICES()\n", - "pad": "\n// Standard usage:\nout = pad( 'a', 5 )\n\n// Left pad:\nout = pad( 'a', 10, { 'lpad': 'b' })\n\n// Right pad:\nout = pad( 'a', 12, { 'rpad': 'b' })\n\n// Center an input string:\nopts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\n\n// Left center:\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\n\n// Right center:\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\n\n// Output string always length `len`:\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\n\n// Pad right, trim right:\nout = pad( 'beep', 2 )\n\n// Pad left, trim left:\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\n\n// Pad both, trim both:\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\n\n// Pad both, trim both starting from left:\nout = pad( 'abcdef', 3, opts )\n\n// Pad both, trim both starting from right:\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n", - "papply": "function add( x, y ) { return x + y; };\nadd2 = papply( add, 2 );\nsum = add2( 3 )\n", - "papplyRight": "function say( text, name ) { return text + ', ' + name + '.'; };\ntoGrace = papplyRight( say, 'Grace Hopper' );\nstr = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n", - "parallel": "function done( error ) { if ( error ) { throw error; } };\nfiles = [ './a.js', './b.js' ];\nparallel( files, done );\n\n// Specify the number of workers:\nopts = { 'workers': 8 };\nparallel( files, opts, done );\n", - "parseJSON": "obj = parseJSON( '{\"beep\":\"boop\"}' )\n\n// Provide a reviver:\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n};\nstr = '{\"beep\":\"boop\",\"a\":\"b\"}';\nout = parseJSON( str, reviver )\n", - "PATH_DELIMITER": "PATH_DELIMITER\n\n// POSIX environment:\npath = '/usr/bin:/bin:/usr/sbin';\nparts = path.split( PATH_DELIMITER )\n\n// Windows environment:\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n", - "PATH_DELIMITER_POSIX": "PATH_DELIMITER_POSIX\nPATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\npaths = PATH.split( PATH_DELIMITER_POSIX )\n", - "PATH_DELIMITER_WIN32": "PATH_DELIMITER_WIN32\nPATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\npaths = PATH.split( PATH_DELIMITER_WIN32 )\n", - "PATH_SEP": "PATH_SEP\n\n// Windows environment:\nparts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n\n// POSIX environment:\nparts = 'foo/bar/baz'.split( PATH_SEP )\n", - "PATH_SEP_POSIX": "PATH_SEP_POSIX\nparts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n", - "PATH_SEP_WIN32": "PATH_SEP_WIN32\nparts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n", - "pcorrtest": "rho = 0.5;\nx = new Array( 300 );\ny = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\n x[ i ] = base.random.normal( 0.0, 1.0 );\n y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n base.sqrt( 1.0 - (rho*rho) ) );\n}\nout = pcorrtest( x, y )\n\n// Print output:\ntable = out.print()\n", - "percentEncode": "out = percentEncode( '☃' )\n", - "PHI": "PHI\n", - "PI": "PI\n", - "PI_SQUARED": "PI_SQUARED\n", - "pick": "obj1 = { 'a': 1, 'b': 2 };\nobj2 = pick( obj1, 'b' )\n", - "pickBy": "function predicate( key, value ) {\n return ( value > 1 );\n};\nobj1 = { 'a': 1, 'b': 2 };\nobj2 = pickBy( obj1, predicate )\n", - "PINF": "PINF\n", - "pkg2alias": "v = pkg2alias( '@stdlib/math/base/special/sin' )\n", - "pkg2related": "v = pkg2related( '@stdlib/math/base/special/sin' )\n", - "PLATFORM": "PLATFORM\n", - "plot": "plot = plot()\n\n// Provide plot data at instantiation:\nx = [[0.10, 0.20, 0.30]];\ny = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n", - "Plot": "plot = Plot()\n\n// Provide plot data at instantiation:\nx = [[0.10, 0.20, 0.30]];\ny = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n", - "pluck": "arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n];\nout = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n];\nout = pluck( arr, 'a', { 'copy': false } )\nbool = ( arr[ 0 ] === out[ 0 ] )\n", - "pop": "\n// Arrays:\narr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nout = pop( arr )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\n\n// Array-like object:\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n", - "prepend": "\n// Arrays:\narr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\n\n// Array-like object:\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n", - "properties": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\nprops = properties( obj )\n", - "propertiesIn": "props = propertiesIn( [] )\n", - "propertyDescriptor": "obj = { 'a': 'b' };\ndesc = propertyDescriptor( obj, 'a' )\n", - "propertyDescriptorIn": "obj = { 'a': 'b' };\ndesc = propertyDescriptorIn( obj, 'a' )\n", - "propertyDescriptors": "obj = { 'a': 'b' };\ndesc = propertyDescriptors( obj )\n", - "propertyDescriptorsIn": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\ndesc = propertyDescriptorsIn( obj )\n", - "propertyNames": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\nkeys = propertyNames( obj )\n", - "propertyNamesIn": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\nkeys = propertyNamesIn( obj )\n", - "propertySymbols": "s = propertySymbols( {} )\n", - "propertySymbolsIn": "s = propertySymbolsIn( [] )\n", - "Proxy": "function get( obj, prop ) { return obj[ prop ] * 2.0 };\nh = { 'get': get };\np = new Proxy( {}, h );\np.a = 3.14;\np.a\n", - "push": "\n// Arrays:\narr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\n\n// Array-like object:\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n", - "quarterOfYear": "q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\n\n// Other ways to supply month:\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n", - "random.iterators.arcsine": "it = random.iterators.arcsine( 0.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.bernoulli": "it = random.iterators.bernoulli( 0.3 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.beta": "it = random.iterators.beta( 1.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.betaprime": "it = random.iterators.betaprime( 1.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.binomial": "it = random.iterators.binomial( 10, 0.3 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.boxMuller": "it = random.iterators.boxMuller();\nr = it.next().value\nr = it.next().value\n", - "random.iterators.cauchy": "it = random.iterators.cauchy( 0.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.chi": "it = random.iterators.chi( 1.5 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.chisquare": "it = random.iterators.chisquare( 1.5 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.cosine": "it = random.iterators.cosine( 0.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.discreteUniform": "it = random.iterators.discreteUniform( 0, 3 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.erlang": "it = random.iterators.erlang( 1, 1.5 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.exponential": "it = random.iterators.exponential( 1.5 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.f": "it = random.iterators.f( 1.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.frechet": "it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.gamma": "it = random.iterators.gamma( 1.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.geometric": "it = random.iterators.geometric( 0.3 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.gumbel": "it = random.iterators.gumbel( 0.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.hypergeometric": "it = random.iterators.hypergeometric( 20, 10, 7 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.improvedZiggurat": "it = random.iterators.improvedZiggurat();\nr = it.next().value\nr = it.next().value\n", - "random.iterators.invgamma": "it = random.iterators.invgamma( 1.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.kumaraswamy": "it = random.iterators.kumaraswamy( 1.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.laplace": "it = random.iterators.laplace( 0.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.levy": "it = random.iterators.levy( 0.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.logistic": "it = random.iterators.logistic( 0.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.lognormal": "it = random.iterators.lognormal( 0.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.minstd": "it = random.iterators.minstd();\nr = it.next().value\nr = it.next().value\n", - "random.iterators.minstdShuffle": "it = random.iterators.minstdShuffle();\nr = it.next().value\nr = it.next().value\n", - "random.iterators.mt19937": "it = random.iterators.mt19937();\nr = it.next().value\nr = it.next().value\n", - "random.iterators.negativeBinomial": "it = random.iterators.negativeBinomial( 10, 0.3 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.normal": "it = random.iterators.normal( 0.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.pareto1": "it = random.iterators.pareto1( 1.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.poisson": "it = random.iterators.poisson( 1.5 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.randi": "it = random.iterators.randi();\nr = it.next().value\nr = it.next().value\n", - "random.iterators.randn": "it = random.iterators.randn();\nr = it.next().value\nr = it.next().value\n", - "random.iterators.randu": "it = random.iterators.randu();\nr = it.next().value\nr = it.next().value\n", - "random.iterators.rayleigh": "it = random.iterators.rayleigh( 1.5 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.t": "it = random.iterators.t( 1.5 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.triangular": "it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.uniform": "it = random.iterators.uniform( 0.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.iterators.weibull": "it = random.iterators.weibull( 1.0, 1.0 );\nr = it.next().value\nr = it.next().value\n", - "random.streams.arcsine": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.arcsine( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.bernoulli": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.bernoulli( 0.5, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.beta": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.beta( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.betaprime": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.betaprime( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.binomial": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.binomial( 20, 0.5, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.boxMuller": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.boxMuller( opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.cauchy": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.cauchy( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.chi": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.chi( 3.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.chisquare": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.chisquare( 3.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.cosine": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.cosine( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.discreteUniform": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.discreteUniform( 2, 5, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.erlang": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.erlang( 2, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.exponential": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.exponential( 3.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.f": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.f( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.gamma": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.gamma( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.geometric": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.geometric( 0.5, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.gumbel": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.gumbel( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.improvedZiggurat": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.improvedZiggurat( opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.invgamma": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.invgamma( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.kumaraswamy": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.kumaraswamy( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.laplace": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.laplace( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.levy": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.levy( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.logistic": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.logistic( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.lognormal": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.lognormal( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.minstd": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.minstd( opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.minstdShuffle": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.minstdShuffle( opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.mt19937": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.mt19937( opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.negativeBinomial": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.negativeBinomial( 20.0, 0.5, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.normal": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.normal( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.pareto1": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.pareto1( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.poisson": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.poisson( 3.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.randi": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.randi( opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.randn": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.randn( opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.randu": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.randu( opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.rayleigh": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.rayleigh( 3.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.t": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.t( 3.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.uniform": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.uniform( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "random.streams.weibull": "function fcn( chunk ) { console.log( chunk.toString() ); };\nopts = { 'iter': 10 };\ns = random.streams.weibull( 2.0, 5.0, opts );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "ranks": "arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nout = ranks( arr )\n\n// Ties are averaged:\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\n\n// Missing values are placed last:\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n", - "RE_BASENAME": "base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]\n", - "RE_BASENAME_POSIX": "base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n", - "RE_BASENAME_WINDOWS": "base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n", - "RE_COLOR_HEXADECIMAL": "bool = RE_COLOR_HEXADECIMAL.test( 'ffffff' )\nbool = RE_COLOR_HEXADECIMAL.test( '000' )\nbool = RE_COLOR_HEXADECIMAL.test( 'beep' )\n", - "RE_DECIMAL_NUMBER": "bool = RE_DECIMAL_NUMBER.test( '1.234' )\nbool = RE_DECIMAL_NUMBER.test( '-1.234' )\nbool = RE_DECIMAL_NUMBER.test( '0.0' )\nbool = RE_DECIMAL_NUMBER.test( '.0' )\nbool = RE_DECIMAL_NUMBER.test( '0' )\nbool = RE_DECIMAL_NUMBER.test( 'beep' )\n\n// Create a RegExp to capture all decimal numbers:\nre = new RegExp( RE_DECIMAL_NUMBER.source, 'g' );\nstr = '1.234 5.6, 7.8';\nout = str.match( re )\n", - "RE_DIRNAME": "dir = RE_DIRNAME.exec( '/foo/bar/index.js' )[ 1 ]\n", - "RE_DIRNAME_POSIX": "dir = RE_DIRNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( 'index.js' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( '.' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( './' )[ 1 ]\ndir = RE_DIRNAME_POSIX.exec( '' )[ 1 ]\n", - "RE_DIRNAME_WINDOWS": "dir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( 'index.js' )[ 1 ]\ndir = RE_DIRNAME_WINDOWS.exec( '' )[ 1 ]\n", - "RE_EOL": "bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n", - "RE_EXTENDED_LENGTH_PATH": "path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = '/c/foo/bar';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\npath = '/foo/bar';\nbool = RE_EXTENDED_LENGTH_PATH.test( path )\n", - "RE_EXTNAME": "dir = RE_EXTNAME.exec( '/foo/bar/index.js' )[ 1 ]\n", - "RE_EXTNAME_POSIX": "ext = RE_EXTNAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( 'index.js' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( '.' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( './' )[ 1 ]\next = RE_EXTNAME_POSIX.exec( '' )[ 1 ]\n", - "RE_EXTNAME_WINDOWS": "ext = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'beep\\\\boop.' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( 'index.js' )[ 1 ]\next = RE_EXTNAME_WINDOWS.exec( '' )[ 1 ]\n", - "RE_FILENAME": "f = '/foo/bar/index.js';\nparts = RE_FILENAME.exec( f ).slice()\n", - "RE_FILENAME_POSIX": "parts = RE_FILENAME_POSIX.exec( '/foo/bar/index.js' ).slice()\nparts = RE_FILENAME_POSIX.exec( './foo/bar/.gitignore' ).slice()\nparts = RE_FILENAME_POSIX.exec( 'foo/file.pdf' ).slice()\nparts = RE_FILENAME_POSIX.exec( '/foo/bar/file' ).slice()\nparts = RE_FILENAME_POSIX.exec( 'index.js' ).slice()\nparts = RE_FILENAME_POSIX.exec( '.' ).slice()\nparts = RE_FILENAME_POSIX.exec( './' ).slice()\nparts = RE_FILENAME_POSIX.exec( '' ).slice()\n", - "RE_FILENAME_WINDOWS": "parts = RE_FILENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( 'index.js' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '.' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( './' ).slice()\nparts = RE_FILENAME_WINDOWS.exec( '' ).slice()\n", - "RE_FUNCTION_NAME": "function beep() { return 'boop'; };\nname = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n", - "RE_NATIVE_FUNCTION": "bool = RE_NATIVE_FUNCTION.test( Date.toString() )\nbool = RE_NATIVE_FUNCTION.test( (function noop() {}).toString() )\n", - "RE_REGEXP": "bool = RE_REGEXP.test( '/^beep$/' )\nbool = RE_REGEXP.test( '/boop' )\n\n// Escape regular expression strings:\nbool = RE_REGEXP.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE_REGEXP.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n", - "RE_UNC_PATH": "path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE_UNC_PATH.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\';\nbool = RE_UNC_PATH.test( path )\npath = '';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE_UNC_PATH.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE_UNC_PATH.test( path )\npath = '//server/share';\nbool = RE_UNC_PATH.test( path )\npath = '/foo/bar';\nbool = RE_UNC_PATH.test( path )\npath = 'foo/bar';\nbool = RE_UNC_PATH.test( path )\npath = './foo/bar';\nbool = RE_UNC_PATH.test( path )\npath = '/foo/../bar';\nbool = RE_UNC_PATH.test( path )\n", - "RE_UTF16_SURROGATE_PAIR": "bool = RE_UTF16_SURROGATE_PAIR.test( 'abc\\uD800\\uDC00def' )\nbool = RE_UTF16_SURROGATE_PAIR.test( 'abcdef' )\n", - "RE_UTF16_UNPAIRED_SURROGATE": "bool = RE_UTF16_UNPAIRED_SURROGATE.test( 'abc' )\nbool = RE_UTF16_UNPAIRED_SURROGATE.test( '\\uD800' )\n", - "RE_WHITESPACE": "bool = RE_WHITESPACE.test( '\\n' )\nbool = RE_WHITESPACE.test( ' ' )\nbool = RE_WHITESPACE.test( 'a' )\n", - "readDir": "function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadDir( './beep/boop', onRead );\n", - "readFile": "function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadFile( './beep/boop.js', onRead );\n", - "readFileList": "function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nfilepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n", - "readJSON": "function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadJSON( './beep/boop.json', onRead );\n", - "readWASM": "function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n};\nreadWASM( './beep/boop.wasm', onRead );\n", - "real": "z = new Complex128( 5.0, 3.0 );\nre = real( z )\n", - "realmax": "m = realmax( 'float16' )\nm = realmax( 'float32' )\n", - "realmin": "m = realmin( 'float16' )\nm = realmin( 'float32' )\n", - "reduce": "function sum( acc, v ) { return acc + v; };\narr = [ 1.0, 2.0, 3.0 ];\nout = reduce( arr, 0, sum )\n", - "reduceAsync": "\n// Basic usage:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\narr = [ 3000, 2500, 1000 ];\nacc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000 ];\nacc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n\n// Process concurrently:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nopts = { 'series': false };\narr = [ 3000, 2500, 1000 ];\nacc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n", - "reduceRight": "function sum( acc, v ) {\n console.log( '%s: %d', acc, v );\n return acc + v;\n};\narr = [ 1.0, 2.0, 3.0 ];\nout = reduceRight( arr, 0, sum );\nout\n", - "reduceRightAsync": "\n// Basic usage:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\narr = [ 1000, 2500, 3000 ];\nacc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\n\n// Limit number of concurrent invocations:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nopts = { 'limit': 2 };\narr = [ 1000, 2500, 3000 ];\nacc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n\n// Process concurrently:\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n};\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n};\nopts = { 'series': false };\narr = [ 1000, 2500, 3000 ];\nacc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n", - "reFromString": "re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n", - "reim": "z = new Complex128( 5.0, 3.0 );\nout = reim( z )\n", - "removeFirst": "out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\n", - "removeLast": "out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\n", - "removePunctuation": "str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nout = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n", - "removeUTF8BOM": "out = removeUTF8BOM( '\\ufeffbeep' )\n", - "removeWords": "out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n\n// Case-insensitive:\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n", - "rename": "function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n};\nrename( './beep/boop.txt', './beep/foo.txt', done );\n", - "reorderArguments": "function foo( a, b, c ) { return [ a, b, c ]; };\nbar = reorderArguments( foo, [ 2, 0, 1 ] );\nout = bar( 1, 2, 3 )\n", - "repeat": "out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n", - "replace": "\n// Standard usage:\nout = replace( 'beep', 'e', 'o' )\n\n// Replacer function:\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nstr = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\n\n// Replace only first match:\nout = replace( 'beep', /e/, 'o' )\n", - "rescape": "str = rescape( '[A-Z]*' )\n", - "resolveParentPath": "function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n};\nresolveParentPath( 'package.json', onPath );\n", - "reverseArguments": "function foo( a, b, c ) { return [ a, b, c ]; };\nbar = reverseArguments( foo );\nout = bar( 1, 2, 3 )\n", - "reverseString": "out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n", - "reviveBasePRNG": "str = JSON.stringify( base.random.mt19937 );\nr = parseJSON( str, reviveBasePRNG )\n", - "reviveBuffer": "str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nbuf = parseJSON( str, reviveBuffer )\n", - "reviveComplex": "str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nz = parseJSON( str, reviveComplex )\n", - "reviveComplex64": "str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nz = parseJSON( str, reviveComplex64 )\n", - "reviveComplex128": "str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nz = parseJSON( str, reviveComplex128 )\n", - "reviveError": "str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nerr = JSON.parse( str, reviveError )\n", - "reviveTypedArray": "str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\narr = parseJSON( str, reviveTypedArray )\n", - "rpad": "out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n", - "rtrim": "out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n", - "safeintmax": "m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n", - "safeintmin": "m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n", - "sample": "out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nbool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\n\n// Set sample size:\nout = sample( [ 3, 6, 9 ], { 'size': 10 })\nout = sample( [ 0, 1 ], { 'size': 20 })\n\n// Draw without replacement:\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 })\nout = sample( [ 0, 1 ], { 'replace': false })\n\n// Assigning non-uniform element probabilities:\nx = [ 1, 2, 3, 4, 5, 6 ];\nprobs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs })\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false })\n", - "SAVOY_STOPWORDS_FIN": "list = SAVOY_STOPWORDS_FIN()\n", - "SAVOY_STOPWORDS_FR": "list = SAVOY_STOPWORDS_FR()\n", - "SAVOY_STOPWORDS_GER": "list = SAVOY_STOPWORDS_GER()\n", - "SAVOY_STOPWORDS_IT": "list = SAVOY_STOPWORDS_IT()\n", - "SAVOY_STOPWORDS_POR": "list = SAVOY_STOPWORDS_POR()\n", - "SAVOY_STOPWORDS_SP": "list = SAVOY_STOPWORDS_SP()\n", - "SAVOY_STOPWORDS_SWE": "list = SAVOY_STOPWORDS_SWE()\n", - "SECONDS_IN_DAY": "days = 3.14;\nsecs = days * SECONDS_IN_DAY\n", - "SECONDS_IN_HOUR": "hrs = 3.14;\nsecs = hrs * SECONDS_IN_HOUR\n", - "SECONDS_IN_MINUTE": "mins = 3.14;\nsecs = mins * SECONDS_IN_MINUTE\n", - "SECONDS_IN_WEEK": "wks = 3.14;\nsecs = wks * SECONDS_IN_WEEK\n", - "secondsInMonth": "num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\n\n// Other ways to supply month:\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n", - "secondsInYear": "num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n", - "setConfigurableReadOnly": "obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", - "setConfigurableReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", - "setConfigurableReadWriteAccessor": "obj = {};\nname = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n", - "setConfigurableWriteOnlyAccessor": "obj = {};\nval = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n", - "setMemoizedReadOnly": "obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n", - "setNonEnumerableProperty": "obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n", - "setNonEnumerableReadOnly": "obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", - "setNonEnumerableReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", - "setNonEnumerableReadWriteAccessor": "obj = {};\nname = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n", - "setNonEnumerableWriteOnlyAccessor": "obj = {};\nval = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n", - "setReadOnly": "obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n", - "setReadOnlyAccessor": "obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n", - "setReadWriteAccessor": "obj = {};\nname = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n", - "setWriteOnlyAccessor": "obj = {};\nval = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n", - "SharedArrayBuffer": "\n// Assuming an environment supports SharedArrayBuffers...\nbuf = new SharedArrayBuffer( 5 )\n", - "shift": "\n// Arrays:\narr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nout = shift( arr )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\n\n// Array-like object:\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n", - "shuffle": "data = [ 1, 2, 3 ];\nout = shuffle( data )\nout = shuffle( data, { 'copy': 'none' });\nbool = ( data === out )\n", - "sizeOf": "s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n", - "some": "arr = [ 0, 0, 1, 2, 3 ];\nbool = some( arr, 3 )\n", - "someBy": "function negative( v ) { return ( v < 0 ); };\narr = [ 1, 2, -3, 4, -1 ];\nbool = someBy( arr, 2, negative )\n", - "someByAsync": "\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\narr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'series': true };\narr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n", - "someByRight": "function negative( v ) { return ( v < 0 ); };\narr = [ -1, 1, -2, 3, 4 ];\nbool = someByRight( arr, 2, negative )\n", - "someByRightAsync": "\n// Basic usage:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\narr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\n\n// Limit number of concurrent invocations:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'limit': 2 };\narr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n\n// Process sequentially:\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n};\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n};\nopts = { 'series': true };\narr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n", - "SOTU": "out = SOTU()\n\n// Retrieve addresses by one or more Presidents...\nopts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\n\n// Retrieve addresses by one or more political parties...\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\n\n// Retrieve addresses from one or more years...\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\n\n// Retrieve addresses from a range of consecutive years...\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n", - "SPACHE_REVISED": "list = SPACHE_REVISED()\n", - "SPAM_ASSASSIN": "data = SPAM_ASSASSIN()\n", - "SparklineBase": "sparkline = new SparklineBase()\n\n// Provide sparkline data at instantiation:\ndata = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n", - "sparsearray2iterator": "it = sparsearray2iterator( [ 1, , 3, 4 ] );\nv = it.next().value\nv = it.next().value\n", - "sparsearray2iteratorRight": "it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nv = it.next().value\nv = it.next().value\n", - "splitStream": "s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n", - "SQRT_EPS": "SQRT_EPS\n", - "SQRT_HALF": "SQRT_HALF\n", - "SQRT_HALF_PI": "SQRT_HALF_PI\n", - "SQRT_PHI": "SQRT_PHI\n", - "SQRT_PI": "SQRT_PI\n", - "SQRT_THREE": "SQRT_THREE\n", - "SQRT_TWO": "SQRT_TWO\n", - "SQRT_TWO_PI": "SQRT_TWO_PI\n", - "Stack": "s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n", - "startcase": "out = startcase( 'beep boop' )\n", - "startsWith": "bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n", - "STOPWORDS_EN": "list = STOPWORDS_EN()\n", - "stridedarray2iterator": "it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nv = it.next().value\nv = it.next().value\n", - "stridedArrayStream": "function fcn( chunk ) { console.log( chunk.toString() ); };\ns = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\no = inspectSinkStream( fcn );\ns.pipe( o );\n", - "string2buffer": "b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n", - "sub2ind": "d = [ 3, 3, 3 ];\nidx = sub2ind( d, 1, 2, 2 )\n", - "SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK": "data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n", - "SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK": "data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n", - "Symbol": "s = ( Symbol ) ? Symbol( 'beep' ) : null\n", - "tabulate": "collection = [ 'beep', 'boop', 'foo', 'beep' ];\nout = tabulate( collection )\n", - "tabulateBy": "function indicator( value ) { return value[ 0 ]; };\ncollection = [ 'beep', 'boop', 'foo', 'beep' ];\nout = tabulateBy( collection, indicator )\n", - "tabulateByAsync": "\n// Basic usage:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\narr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\n\n// Limit number of concurrent invocations:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nopts = { 'limit': 2 };\narr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n\n// Process sequentially:\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nopts = { 'series': true };\narr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n", - "tic": "t = tic()\n", - "timeit": "code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n};\ntimeit( code, done )\n", - "tmpdir": "dir = tmpdir()\n", - "toc": "start = tic();\ndelta = toc( start )\n", - "tokenize": "out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n", - "transformStream": "s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n", - "trim": "out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n", - "trycatch": "function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n};\nz = trycatch( x, -1.0 )\n", - "trycatchAsync": "function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n};\ntrycatchAsync( x, 'boop', done )\n", - "tryFunction": "function fcn() { throw new Error( 'beep boop' ); };\nf = tryFunction( fcn );\nout = f();\nout.message\n", - "tryRequire": "out = tryRequire( '_unknown_module_id_' )\n", - "trythen": "function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n};\nfunction y() {\n return -1.0;\n};\nz = trythen( x, y )\n", - "trythenAsync": "function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n};\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\ntrythenAsync( x, y, done )\n", - "ttest": "\n// One-sample t-test:\nrnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 });\nx = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n}\nout = ttest( x )\n\n// Paired t-test:\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 });\nx = new Array( 100 );\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n}\nout = ttest( x, y )\n\n// Print formatted output:\ntable = out.print()\n\n// Choose custom significance level:\narr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 });\ntable = out.print()\n\n// Test for a mean equal to five:\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 })\n\n// Perform one-sided tests:\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' });\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' });\ntable = out.print()\n", - "ttest2": "\n// Student's sleep data:\nx = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\ny = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nout = ttest2( x, y )\n\n// Print table output:\ntable = out.print()\n\n// Choose a different significance level than `0.05`:\nout = ttest2( x, y, { 'alpha': 0.1 });\ntable = out.print()\n\n// Perform one-sided tests:\nout = ttest2( x, y, { 'alternative': 'less' });\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' });\ntable = out.print()\n\n// Run tests with equal variances assumption:\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' });\ntable = out.print()\n\n// Test for a difference in means besides zero:\nrnorm = base.random.normal.factory({ 'seed': 372 });\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n}\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n}\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' })\n", - "TWO_PI": "TWO_PI\n", - "typedarray": "arr = typedarray()\narr = typedarray( 'float32' )\n", - "typedarray2json": "arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\njson = typedarray2json( arr )\n", - "typedarrayComplexCtors": "ctor = typedarrayComplexCtors( 'complex64' )\nctor = typedarrayComplexCtors( 'float32' )\n", - "typedarrayComplexDataTypes": "out = typedarrayComplexDataTypes()\n", - "typedarrayCtors": "ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n", - "typedarrayDataTypes": "out = typedarrayDataTypes()\n", - "typedarraypool": "arr = typedarraypool()\narr = typedarraypool( 'float32' )\n", - "typemax": "m = typemax( 'int8' )\nm = typemax( 'uint32' )\n", - "typemin": "m = typemin( 'int8' )\nm = typemin( 'uint32' )\n", - "typeOf": "\n// Built-ins:\nt = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\n\n// Arguments object:\nfunction beep() { return arguments; };\nt = typeOf( beep() )\n\n// Node.js Buffer object:\nt = typeOf( new Buffer( 10 ) )\n\n// Custom constructor:\nfunction Person() { return this };\nt = typeOf( new Person() )\n\n// Anonymous constructor:\nFoo = function () { return this; };\nt = typeOf( new Foo() )\n", - "UINT8_MAX": "UINT8_MAX\n", - "UINT8_NUM_BYTES": "UINT8_NUM_BYTES\n", - "Uint8Array": "arr = new Uint8Array()\n", - "Uint8ClampedArray": "arr = new Uint8ClampedArray()\n", - "UINT16_MAX": "UINT16_MAX\n", - "UINT16_NUM_BYTES": "UINT16_NUM_BYTES\n", - "Uint16Array": "arr = new Uint16Array()\n", - "UINT32_MAX": "UINT32_MAX\n", - "UINT32_NUM_BYTES": "UINT32_NUM_BYTES\n", - "Uint32Array": "arr = new Uint32Array()\n", - "umask": "mask = umask()\nmask = umask( { 'symbolic': true } )\n", - "uncapitalize": "out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n", - "uncapitalizeKeys": "obj = { 'AA': 1, 'BB': 2 };\nout = uncapitalizeKeys( obj )\n", - "uncurry": "function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n};\nfcn = uncurry( addX );\nsum = fcn( 2, 3 )\n\n// To enforce a fixed number of parameters, provide an `arity` argument:\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n};\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\n\n// To specify an execution context, provide a `thisArg` argument:\nfunction addX( x ) {\n this.x = x;\n return addY;\n};\nfunction addY( y ) {\n return this.x + y;\n};\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n", - "uncurryRight": "function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n};\nfcn = uncurryRight( addX );\nsum = fcn( 3, 2 )\n\n// To enforce a fixed number of parameters, provide an `arity` argument:\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n};\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\n\n// To specify an execution context, provide a `thisArg` argument:\nfunction addY( y ) {\n this.y = y;\n return addX;\n};\nfunction addX( x ) {\n return x + this.y;\n};\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n", - "UNICODE_MAX": "UNICODE_MAX\n", - "UNICODE_MAX_BMP": "UNICODE_MAX_BMP\n", - "UnicodeColumnChartSparkline": "data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nchart = new UnicodeColumnChartSparkline( data );\nchart.render()\n", - "UnicodeLineChartSparkline": "data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nchart = new UnicodeLineChartSparkline( data );\nchart.render()\n", - "UnicodeSparkline": "data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nchart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n", - "UnicodeTristateChartSparkline": "data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nchart = new UnicodeTristateChartSparkline( data );\nchart.render()\n", - "UnicodeUpDownChartSparkline": "data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nchart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n", - "UnicodeWinLossChartSparkline": "data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nchart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n", - "unlink": "function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n};\nunlink( './beep/boop.txt', done );\n", - "unshift": "\n// Arrays:\narr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\n\n// Typed arrays:\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\n\n// Array-like object:\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n", - "until": "function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n", - "untilAsync": "function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nuntilAsync( predicate, fcn, done )\n", - "untilEach": "function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\narr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n", - "untilEachRight": "function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\narr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n", - "unzip": "\n// Basic usage:\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr )\n\n// Provide indices:\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n", - "uppercase": "out = uppercase( 'bEEp' )\n", - "uppercaseKeys": "obj = { 'a': 1, 'b': 2 };\nout = uppercaseKeys( obj )\n", - "US_STATES_ABBR": "list = US_STATES_ABBR()\n", - "US_STATES_CAPITALS": "list = US_STATES_CAPITALS()\n", - "US_STATES_CAPITALS_NAMES": "out = US_STATES_CAPITALS_NAMES()\n", - "US_STATES_NAMES": "list = US_STATES_NAMES()\n", - "US_STATES_NAMES_CAPITALS": "out = US_STATES_NAMES_CAPITALS()\n", - "utf16ToUTF8Array": "str = '☃';\nout = utf16ToUTF8Array( str )\n", - "vartest": "x = [ 610, 610, 550, 590, 565, 570 ];\ny = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nout = vartest( x, y )\n\n// Print table output:\ntable = out.print()\n", - "waterfall": "function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nfcns = [ foo, bar ];\nwaterfall( fcns, done );\n", - "whileAsync": "function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n};\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n};\nwhileAsync( predicate, fcn, done )\n", - "whileEach": "function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\narr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n", - "whileEachRight": "function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\narr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n", - "whilst": "function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n", - "writableProperties": "function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nobj = new Foo();\nprops = writableProperties( obj )\n", - "writablePropertiesIn": "props = writablePropertiesIn( [] )\n", - "writablePropertyNames": "obj = { 'a': 'b' };\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nkeys = writablePropertyNames( obj )\n", - "writablePropertyNamesIn": "obj = { 'a': 'b' };\ndesc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nkeys = writablePropertyNamesIn( obj )\n", - "writablePropertySymbols": "obj = {};\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nsym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nsymbols = writablePropertySymbols( obj )\n", - "writablePropertySymbolsIn": "obj = {};\ndesc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nsym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nsymbols = writablePropertySymbolsIn( obj )\n", - "writeFile": "function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n};\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n", - "zip": "\n// Basic usage:\nout = zip( [ 1, 2 ], [ 'a', 'b' ] )\n\n// Turn off truncation:\nopts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n", - "ztest": "\n// One-sample z-test:\nrnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 });\nx = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n}\nout = ztest( x, 2.0 )\n\n// Choose custom significance level and print output:\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 });\ntable = out.print()\n\n// Test for a mean equal to five:\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 })\n\n// Perform one-sided tests:\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' })\nout = ztest( arr, 1.0, { 'alternative': 'greater' })\n", - "ztest2": "\n// Drawn from Normal(0,2):\nx = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n// Drawn from Normal(1,2):\ny = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nout = ztest2( x, y, 2.0, 2.0 )\n\n// Print table output:\ntable = out.print()\n\n// Choose a different significance level than `0.05`:\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 });\ntable = out.print()\n\n// Perform one-sided tests:\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' });\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' });\ntable = out.print()\n\n// Test for a difference in means besides zero:\nrnorm = base.random.normal.factory({ 'seed': 372 });\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n}\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n}\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 })\n" -}; - -module.exports = db; diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/index.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/index.js index 3e161988754b..a1caf6280c02 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/index.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/index.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -19,22 +19,22 @@ 'use strict'; /** -* REPL examples. +* Return an example associated with a provided alias. * * @module @stdlib/repl/code-blocks * * @example -* var examples = require( '@stdlib/repl/code-blocks' ); +* var example = require( '@stdlib/repl/code-blocks' ); * -* var o = examples(); -* // returns {...} +* var out = example( 'base.sin' ); +* // returns */ // MODULES // -var examples = require( './main.js' ); +var example = require( './main.js' ); // EXPORTS // -module.exports = examples; +module.exports = example; diff --git a/lib/node_modules/@stdlib/repl/code-blocks/lib/main.js b/lib/node_modules/@stdlib/repl/code-blocks/lib/main.js index afa9f149b4ed..aeee66fe89f2 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/lib/main.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/lib/main.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -20,26 +20,35 @@ // MODULES // -var copy = require( '@stdlib/utils/copy' ); -var EXAMPLES = require( './db.js' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var ALIAS_TO_EXAMPLE = require( './../data/data.json' ); // MAIN // /** -* Returns REPL examples. +* Returns an example associated with a specified alias. * -* @returns {Object} examples +* @param {string} alias - alias +* @throws {TypeError} must provide a string +* @returns {(string|null)} example * * @example -* var o = examples(); -* // returns {...} +* var out = example( 'base.sin' ); +* // returns */ -function examples() { - return copy( EXAMPLES ); +function example( alias ) { + if ( !isString( alias ) ) { + throw new TypeError( 'invalid argument. Must provide a string. Value: `' + alias + '`.' ); + } + if ( hasOwnProp( ALIAS_TO_EXAMPLE, alias ) ) { + return ALIAS_TO_EXAMPLE[ alias ]; + } + return null; } // EXPORTS // -module.exports = examples; +module.exports = example; diff --git a/lib/node_modules/@stdlib/repl/code-blocks/package.json b/lib/node_modules/@stdlib/repl/code-blocks/package.json index f3ba7ee5c080..db0ab700c155 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/package.json +++ b/lib/node_modules/@stdlib/repl/code-blocks/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/repl/code-blocks", "version": "0.0.0", - "description": "REPL examples.", + "description": "Return an example associated with a provided alias.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", @@ -13,14 +13,20 @@ "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" } ], + "bin": { + "stdlib-alias-help": "./bin/cli" + }, "main": "./lib", "directories": { "benchmark": "./benchmark", + "bin": "./bin", + "data": "./data", + "doc": "./docs", "example": "./examples", "lib": "./lib", - "scripts": "./scripts", "test": "./test" }, + "types": "./docs/types", "scripts": {}, "homepage": "https://github.com/stdlib-js/stdlib", "repository": { diff --git a/lib/node_modules/@stdlib/repl/code-blocks/scripts/build.js b/lib/node_modules/@stdlib/repl/code-blocks/scripts/build.js index 815d3483e1bd..6bdf12102c56 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/scripts/build.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/scripts/build.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -25,28 +25,17 @@ var logger = require( 'debug' ); var objectKeys = require( '@stdlib/utils/keys' ); var replace = require( '@stdlib/string/replace' ); var writeFile = require( '@stdlib/fs/write-file' ).sync; -var licenseHeader = require( '@stdlib/_tools/licenses/header' ); -var docs = require( '@stdlib/repl/help' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var help = require( '@stdlib/repl/help' ); // VARIABLES // -var debug = logger( 'repl:examples:build' ); +var debug = logger( 'repl:code-blocks:build' ); -// Examples output file path: -var EXAMPLES_OUTPUT = resolvePath( __dirname, '..', 'lib', 'db.js' ); - -// License header options: -var HEADER_OPTIONS = { - 'copyright': 'The Stdlib Authors', - 'year': ( new Date() ).getFullYear() -}; - -// Output file preamble: -var PREAMBLE = '/* eslint-disable quotes, max-lines */\n\n'+licenseHeader( 'Apache-2.0', 'js', HEADER_OPTIONS )+'\n/*\n* This file is generated by scripts/build.js.\n*/\n\'use strict\';\n\nvar db = '; - -// Output file append: -var APPEND = 'module.exports = db;\n'; +// Output file paths: +var OUTPUT_JSON = resolvePath( __dirname, '..', 'data', 'data.json' ); +var OUTPUT_CSV = resolvePath( __dirname, '..', 'data', 'data.csv' ); // Identifier for inserting 'See Also' links: var SEE_ALSO = '\n See Also\n --------\n'; @@ -78,43 +67,46 @@ var RE_IDENTATION = /^(\s{4})/; // Regular expression for indentation (global): var RE_IDENTATION_GLOBAL = /^(\s{4})/g; -// Regular expression for variable declaration: -var RE_VAR_DECLARATION = /^(var\s+)/; - // FUNCTIONS // /** -* Generates a hash for REPL examples. +* Main execution sequence. * * @private -* @param {Object} docs - hash containing REPL help text */ -function createExamples( docs ) { - var aliases; +function main() { + var ALIASES; var alias; var fopts; var lines; var line; + var json; + var keys; + var csv; var acc; var txt; - var out; var flg; + var tmp; var i; var j; + debug( 'Generating REPL examples.' ); fopts = { 'encoding': 'utf8' }; - out = {}; + json = {}; - aliases = objectKeys( docs ); - for ( i = 0; i < aliases.length; i++ ) { - alias = aliases[ i ]; + ALIASES = aliases(); + for ( i = 0; i < ALIASES.length; i++ ) { + alias = ALIASES[ i ]; debug( 'Loading REPL text: %s', alias ); - txt = docs[ alias ]; - + txt = help( alias ); + if ( txt === null ) { + debug( 'Unable to resolve alias help text: %s', alias ); + continue; + } debug( 'Extracting examples section.' ); lines = txt.split( '\n' ); flg = false; @@ -144,7 +136,6 @@ function createExamples( docs ) { line = replace( line, RE_PROMPT, '' ); line = replace( line, RE_CONTINUATION, '' ); line = replace( line, RE_IDENTATION_GLOBAL, ' ' ); - line = replace( line, RE_VAR_DECLARATION, '' ); // NOTE: the REPL silences output when declaring a variable. So we remove any variable declarations here. acc += line + '\n'; } else if ( RE_COMMENT.test( line ) ) { line = replace( line, RE_IDENTATION, '' ); @@ -159,22 +150,21 @@ function createExamples( docs ) { if ( acc === '' ) { debug( 'Unable to extract an examples section.' ); } else { - out[ alias ] = acc; + json[ alias ] = acc; } } - debug( 'Writing REPL example hash to file.' ); - out = PREAMBLE+JSON.stringify( out, null, '\t' )+';\n\n'+APPEND; - writeFile( EXAMPLES_OUTPUT, out, fopts ); -} - -/** -* Main execution sequence. -* -* @private -*/ -function main() { - debug( 'Generating REPL examples.' ); - createExamples( docs() ); + debug( 'Writing to JSON file.' ); + writeFile( OUTPUT_JSON, JSON.stringify( json ), fopts ); + + debug( 'Writing to CSV file.' ); + keys = objectKeys( json ); + csv = ''; + for ( i = 0; i < keys.length; i++ ) { + tmp = replace( json[ keys[i] ], /\r?\n/g, '\\n' ); + tmp = replace( tmp, '"', '\\"' ); + csv += keys[ i ] + ',"' + tmp + '"\n'; // Note: ensures trailing newline + } + writeFile( OUTPUT_CSV, csv, fopts ); } diff --git a/lib/node_modules/@stdlib/repl/code-blocks/test/test.cli.js b/lib/node_modules/@stdlib/repl/code-blocks/test/test.cli.js new file mode 100644 index 000000000000..0e4b59e6bdc5 --- /dev/null +++ b/lib/node_modules/@stdlib/repl/code-blocks/test/test.cli.js @@ -0,0 +1,184 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var exec = require( 'child_process' ).exec; +var tape = require( 'tape' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var IS_WINDOWS = require( '@stdlib/assert/is-windows' ); +var readFileSync = require( '@stdlib/fs/read-file' ).sync; + + +// VARIABLES // + +var fpath = resolve( __dirname, '..', 'bin', 'cli' ); +var opts = { + 'skip': IS_BROWSER || IS_WINDOWS +}; + + +// FIXTURES // + +var PKG_VERSION = require( './../package.json' ).version; + + +// TESTS // + +tape( 'command-line interface', function test( t ) { + t.ok( true, __filename ); + t.end(); +}); + +tape( 'when invoked with a `--help` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '--help' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-h` flag, the command-line interface prints the help text to `stderr`', opts, function test( t ) { + var expected; + var cmd; + + expected = readFileSync( resolve( __dirname, '..', 'docs', 'usage.txt' ), { + 'encoding': 'utf8' + }); + cmd = [ + process.execPath, + fpath, + '-h' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), expected+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `--version` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '--version' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'when invoked with a `-V` flag, the command-line interface prints the version to `stderr`', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + '-V' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + t.strictEqual( stdout.toString(), '', 'does not print to `stdout`' ); + t.strictEqual( stderr.toString(), PKG_VERSION+'\n', 'expected value' ); + } + t.end(); + } +}); + +tape( 'the command-line interface prints an example as text', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + 'base.sin' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.fail( error.message ); + } else { + stdout = stdout.toString().split( '\n' ); + + // Greater than 1 in order to include the trailing newline: + t.strictEqual( stdout.length > 1, true, 'prints text' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + } + t.end(); + } +}); + +tape( 'if unable to resolve an example, the command-line interface sets a non-zero exit code', opts, function test( t ) { + var cmd = [ + process.execPath, + fpath, + 'fjaldfjadljfeoejreandfljasdfjadsfjs' + ]; + + exec( cmd.join( ' ' ), done ); + + function done( error, stdout, stderr ) { + if ( error ) { + t.pass( error.message ); + t.strictEqual( error.code, 1, 'expected exit code' ); + } + t.strictEqual( stdout.toString(), '', 'does not print to` stdout`' ); + t.strictEqual( stderr.toString(), '', 'does not print to `stderr`' ); + t.end(); + } +}); diff --git a/lib/node_modules/@stdlib/repl/code-blocks/test/test.js b/lib/node_modules/@stdlib/repl/code-blocks/test/test.js index 579a5e3d8561..5b6c7484a6b5 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/test/test.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/test/test.js @@ -1,7 +1,7 @@ /** * @license Apache-2.0 * -* Copyright (c) 2018 The Stdlib Authors. +* Copyright (c) 2019 The Stdlib Authors. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. @@ -21,28 +21,73 @@ // MODULES // var tape = require( 'tape' ); -var isPlainObject = require( '@stdlib/assert/is-plain-object' ); -var examples = require( './../lib' ); +var aliases = require( '@stdlib/namespace/aliases' ); +var DATA = require( './../data/data.json' ); +var example = require( './../lib' ); // TESTS // tape( 'main export is a function', function test( t ) { t.ok( true, __filename ); - t.strictEqual( typeof examples, 'function', 'main export is a function' ); + t.strictEqual( typeof example, 'function', 'main export is a function' ); t.end(); }); -tape( 'the function returns REPL examples', function test( t ) { - var o1; - var o2; +tape( 'the function throws an error if not provided a string', function test( t ) { + var values; + var i; - o1 = examples(); - t.strictEqual( isPlainObject( o1 ), true, 'returns an object' ); + values = [ + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + example( value ); + }; + } +}); + +tape( 'the function returns an example as text', function test( t ) { + var expected; + var actual; + var list; + var i; + + list = aliases(); + for ( i = 0; i < list.length; i++ ) { + expected = DATA[ list[i] ]; + actual = example( list[i] ); + t.strictEqual( typeof actual, 'string', 'returns a string' ); + t.strictEqual( actual, expected, 'returns expected value for '+list[i] ); + } + t.end(); +}); - o2 = examples(); - t.strictEqual( isPlainObject( o2 ), true, 'returns an object' ); - t.notEqual( o1, o2, 'returns new reference' ); +tape( 'the function returns `null` if provided an unrecognized alias', function test( t ) { + var values; + var i; + values = [ + 'adfkaljdfdsafs', + 'adklfadjflajdslfjalsdf', + 'adflkajdlkfjasdlkfjsadlkfjlasdjflsdjfla' + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( example( values[ i ] ), null, 'returns expected value' ); + } t.end(); }); From a5ed4ce9abee7faf43ae5f0ab5421f8d494f5bf7 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 19:33:32 -0700 Subject: [PATCH 116/142] Use temporary workaround to allow current REPL usage --- lib/node_modules/@stdlib/repl/server/lib/context.js | 6 +----- lib/node_modules/@stdlib/repl/server/lib/docs.js | 9 ++------- lib/node_modules/@stdlib/repl/server/lib/examples.js | 9 ++------- 3 files changed, 5 insertions(+), 19 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/server/lib/context.js b/lib/node_modules/@stdlib/repl/server/lib/context.js index b11d34c40bb4..791d8529da50 100644 --- a/lib/node_modules/@stdlib/repl/server/lib/context.js +++ b/lib/node_modules/@stdlib/repl/server/lib/context.js @@ -27,8 +27,6 @@ var deepGet = require( '@stdlib/utils/deep-get' ); var help = require( './functions/help.js' ); var example = require( './functions/example.js' ); var namespace = require( './functions/namespace.js' ); -var alias2pkg = require( './functions/alias2pkg.js' ); -var pkg2alias = require( './functions/pkg2alias.js' ); var NAMESPACE = require( './namespace.js' ); @@ -56,9 +54,7 @@ function extend( repl ) { tmp = { 'help': help, 'example': example( repl ), - 'namespace': namespace, - 'alias2pkg': alias2pkg, - 'pkg2alias': pkg2alias + 'namespace': namespace }; paths = []; for ( i = 0; i < NAMESPACE.length; i++ ) { diff --git a/lib/node_modules/@stdlib/repl/server/lib/docs.js b/lib/node_modules/@stdlib/repl/server/lib/docs.js index 8f182eb5a914..0621bb27c7a5 100644 --- a/lib/node_modules/@stdlib/repl/server/lib/docs.js +++ b/lib/node_modules/@stdlib/repl/server/lib/docs.js @@ -20,14 +20,9 @@ // MODULES // -var help = require( '@stdlib/repl/help' ); - - -// MAIN // - -var out = help(); +var help = require( '@stdlib/repl/help/data/data.json' ); // EXPORTS // -module.exports = out; +module.exports = help; diff --git a/lib/node_modules/@stdlib/repl/server/lib/examples.js b/lib/node_modules/@stdlib/repl/server/lib/examples.js index d81c0428f908..b1b2024883c7 100644 --- a/lib/node_modules/@stdlib/repl/server/lib/examples.js +++ b/lib/node_modules/@stdlib/repl/server/lib/examples.js @@ -20,14 +20,9 @@ // MODULES // -var examples = require( '@stdlib/repl/code-blocks' ); - - -// MAIN // - -var out = examples(); +var examples = require( '@stdlib/repl/code-blocks/data/data.json' ); // EXPORTS // -module.exports = out; +module.exports = examples; From 885a2e875419b3a8f65bac6908501f74717eab23 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 20:13:45 -0700 Subject: [PATCH 117/142] Fix writing to REPL and add support for printing help text --- .../@stdlib/repl/ctor/lib/create_context.js | 45 ++++++++++++++----- 1 file changed, 34 insertions(+), 11 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 34dcd1d173c8..908eea781270 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -33,6 +33,7 @@ var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); var alias2related = require( '@stdlib/namespace/alias2related' ); +var alias2help = require( '@stdlib/repl/help' ); var indexOf = require( './index_of.js' ); var createRequire = require( './create_require.js' ); var HELP_TEXT = require( './help_text.js' ); @@ -50,7 +51,7 @@ var debug = logger( 'repl:context' ); // Cache references to module methods (WARNING: use of *private* methods exposed on the `Module` object; thus, breakage is possible!): var resolveLookupPaths = Module._resolveLookupPaths; -// List project aliases which are overridden/wrapped to provide behavior tailored to the REPL environment: +// List of project aliases which are overridden/wrapped to provide behavior tailored to the REPL environment: var OVERRIDES = [ 'alias2pkg', 'alias2related' @@ -165,7 +166,7 @@ function createContext( repl ) { */ function onAlias2Pkg( alias ) { var aliases; - var pkg; + var out; var N; var i; @@ -173,19 +174,19 @@ function createContext( repl ) { N = aliases.length; if ( isString( alias ) ) { - pkg = alias2pkg( alias ); + out = alias2pkg( alias ); } // If provided an `alias` which is not a string or we failed to resolve a package name based on the provided string value, we try to resolve a string alias (and subsequently a corresponding package name) by searching the list of cached references of global variables/properties... - if ( !pkg ) { + if ( !out ) { i = indexOf( N/2, aliases, 2, 1, alias ); if ( i >= 0 ) { - pkg = alias2pkg( aliases[ i-1 ] ); + out = alias2pkg( aliases[ i-1 ] ); } } - if ( pkg ) { - return pkg; + if ( out ) { + return out; } - console.error( 'Error: unrecognized alias.' ); // eslint-disable-line no-console + repl._ostream.write( 'Error: unrecognized alias.\n' ); } /** @@ -215,7 +216,7 @@ function createContext( repl ) { } } if ( out === void 0 || out === null ) { - console.error( 'Error: unrecognized alias.' ); // eslint-disable-line no-console + repl._ostream.write( 'Error: unrecognized alias.\n' ); return; } if ( out.length ) { @@ -250,12 +251,34 @@ function createContext( repl ) { * @returns {void} */ function onHelp( alias ) { + var aliases; + var out; + var N; + var i; if ( arguments.length === 0 ) { repl._ostream.write( HELP_TEXT ); return; } - // TODO: add support for printing help text; first look through project namespace and then REPL-specific namespace - console.log( String( alias ) ); + aliases = repl._aliases; + N = aliases.length; + + if ( isString( alias ) ) { + out = alias2help( alias ); + } + // If provided an `alias` which is not a string or we failed to resolve a package name based on the provided string value, we try to resolve a string alias (and subsequently a corresponding package name) by searching the list of cached references of global variables/properties... + if ( !out ) { + i = indexOf( N/2, aliases, 2, 1, alias ); + if ( i >= 0 ) { + out = alias2help( aliases[ i-1 ] ); + } + } + // TODO: add support for printing help text for REPL-specific namespace + + if ( out ) { + repl._ostream.write( out+'\n' ); + return; + } + repl._ostream.write( 'Error: no help information available.\n' ); } /** From 1a400d96e5bc623fb870a493154eb64953935758 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 20:17:08 -0700 Subject: [PATCH 118/142] Update error messages --- lib/node_modules/@stdlib/repl/ctor/lib/create_context.js | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 908eea781270..87c82f6ca15a 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -186,7 +186,7 @@ function createContext( repl ) { if ( out ) { return out; } - repl._ostream.write( 'Error: unrecognized alias.\n' ); + repl._ostream.write( 'Error: unrecognized alias. Alias: `'+alias+'`.\n' ); } /** @@ -216,7 +216,7 @@ function createContext( repl ) { } } if ( out === void 0 || out === null ) { - repl._ostream.write( 'Error: unrecognized alias.\n' ); + repl._ostream.write( 'Error: unrecognized alias. Alias: `'+alias+'`.\n' ); return; } if ( out.length ) { @@ -278,7 +278,7 @@ function createContext( repl ) { repl._ostream.write( out+'\n' ); return; } - repl._ostream.write( 'Error: no help information available.\n' ); + repl._ostream.write( 'Error: no help information available. Alias: `'+alias+'`.\n' ); } /** From fe2d684d6db0c786007e3af7e05ef43db9cb26fd Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 20:19:15 -0700 Subject: [PATCH 119/142] Guard against missing help texts --- .../@stdlib/repl/code-blocks/benchmark/benchmark.js | 8 ++++---- lib/node_modules/@stdlib/repl/help/benchmark/benchmark.js | 8 ++++---- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/code-blocks/benchmark/benchmark.js b/lib/node_modules/@stdlib/repl/code-blocks/benchmark/benchmark.js index 5281feb9c100..eb6ea9fd9329 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/benchmark/benchmark.js @@ -39,13 +39,13 @@ bench( pkg, function benchmark( b ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { v = example( values[ i%values.length ] ); - if ( typeof v !== 'string' ) { - b.fail( 'should return a string' ); + if ( typeof v !== 'string' && v !== null ) { + b.fail( 'should return a string or null' ); } } b.toc(); - if ( !isString( v ) ) { - b.fail( 'should return a string' ); + if ( !isString( v ) && v !== null ) { + b.fail( 'should return a string or null' ); } b.pass( 'benchmark finished' ); b.end(); diff --git a/lib/node_modules/@stdlib/repl/help/benchmark/benchmark.js b/lib/node_modules/@stdlib/repl/help/benchmark/benchmark.js index 3461d4f0646b..d7645f61424c 100644 --- a/lib/node_modules/@stdlib/repl/help/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/repl/help/benchmark/benchmark.js @@ -39,13 +39,13 @@ bench( pkg, function benchmark( b ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { v = help( values[ i%values.length ] ); - if ( typeof v !== 'string' ) { - b.fail( 'should return a string' ); + if ( typeof v !== 'string' && v !== null ) { + b.fail( 'should return a string or null' ); } } b.toc(); - if ( !isString( v ) ) { - b.fail( 'should return a string' ); + if ( !isString( v ) && v !== null ) { + b.fail( 'should return a string or null' ); } b.pass( 'benchmark finished' ); b.end(); From b511a536b2d4da157fc7f1f69ff435ab940739e0 Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 20:21:55 -0700 Subject: [PATCH 120/142] Guard against missing help texts --- lib/node_modules/@stdlib/repl/code-blocks/test/test.js | 4 +++- lib/node_modules/@stdlib/repl/help/test/test.js | 4 +++- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/code-blocks/test/test.js b/lib/node_modules/@stdlib/repl/code-blocks/test/test.js index 5b6c7484a6b5..d59d63b02d61 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/test/test.js +++ b/lib/node_modules/@stdlib/repl/code-blocks/test/test.js @@ -70,8 +70,10 @@ tape( 'the function returns an example as text', function test( t ) { list = aliases(); for ( i = 0; i < list.length; i++ ) { expected = DATA[ list[i] ]; + if ( expected === void 0 ) { + expected = null; + } actual = example( list[i] ); - t.strictEqual( typeof actual, 'string', 'returns a string' ); t.strictEqual( actual, expected, 'returns expected value for '+list[i] ); } t.end(); diff --git a/lib/node_modules/@stdlib/repl/help/test/test.js b/lib/node_modules/@stdlib/repl/help/test/test.js index 91e411c20c96..d03638abac91 100644 --- a/lib/node_modules/@stdlib/repl/help/test/test.js +++ b/lib/node_modules/@stdlib/repl/help/test/test.js @@ -70,8 +70,10 @@ tape( 'the function returns help text', function test( t ) { list = aliases(); for ( i = 0; i < list.length; i++ ) { expected = DATA[ list[i] ]; + if ( expected === void 0 ) { + expected = null; + } actual = help( list[i] ); - t.strictEqual( typeof actual, 'string', 'returns a string' ); t.strictEqual( actual, expected, 'returns expected value for '+list[i] ); } t.end(); From 883a3dc57218f42bf060ca3622adb0de2ed7bc3e Mon Sep 17 00:00:00 2001 From: kgryte Date: Thu, 21 Mar 2019 21:35:44 -0700 Subject: [PATCH 121/142] Remove file --- lib/node_modules/@stdlib/repl/ctor/docs/namespace.txt | 8 -------- 1 file changed, 8 deletions(-) delete mode 100644 lib/node_modules/@stdlib/repl/ctor/docs/namespace.txt diff --git a/lib/node_modules/@stdlib/repl/ctor/docs/namespace.txt b/lib/node_modules/@stdlib/repl/ctor/docs/namespace.txt deleted file mode 100644 index 21ab78077f34..000000000000 --- a/lib/node_modules/@stdlib/repl/ctor/docs/namespace.txt +++ /dev/null @@ -1,8 +0,0 @@ - -namespace() - Lists namespace contents. - - Examples - -------- - > namespace() - From 8fc270491de01262c618150a850c729b65b06281 Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 22 Mar 2019 00:26:22 -0700 Subject: [PATCH 122/142] Add command for asserting whether a string is a keyword --- .../@stdlib/repl/ctor/lib/create_context.js | 53 +++++++++++++++++++ 1 file changed, 53 insertions(+) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 87c82f6ca15a..c9a5169a437f 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -27,8 +27,10 @@ var vm = require( 'vm' ); var Console = require( 'console' ).Console; var logger = require( 'debug' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var getGlobal = require( '@stdlib/utils/global' ); var objectKeys = require( '@stdlib/utils/keys' ); +var propertyDescriptor = require( '@stdlib/utils/property-descriptor' ); var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-only-property' ); var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); @@ -123,6 +125,7 @@ function createContext( repl ) { [ 'ans', onAns, true ], [ 'clear', onClear, false ], [ 'help', onHelp, false ], + [ 'isKeyword', isKeyword, false ], [ 'load', onLoad, false ], [ 'quit', onQuit, false ] ]; @@ -281,6 +284,56 @@ function createContext( repl ) { repl._ostream.write( 'Error: no help information available. Alias: `'+alias+'`.\n' ); } + /** + * Returns a boolean indicating whether a string is a reserved keyword in the REPL environment. + * + * ## Notes + * + * - This function supports nested keyword paths (e.g., `base.sin`). + * + * @private + * @param {string} keyword - string to test + * @returns {(boolean|void)} boolean indicating whether a string is a reserved keyword + */ + function isKeyword( keyword ) { + var desc; + var err; + var o; + var i; + var k; + if ( !isString( keyword ) ) { + err = new TypeError( 'invalid argument. Must provide a string. Value: `'+keyword+'`.' ); + debug( 'Error: %s', err.message ); + repl._ostream.write( 'Error: '+err.message+'\n' ); + return; + } + // Our proxy for determining whether a value is a keyword is whether the value is read-only property on the `context` object, as any properties we have added to the `context` object are read-only (note, however, that, in a non-sandboxed environment, the `global` object may have read-only properties we have *not* introduced; meaning, some values which may be flagged as "keywords" were not introduced by us): + keyword = keyword.split( '.' ); + o = context; + for ( i = 0; i < keyword.length-1; i++ ) { + k = keyword[ i ]; + if ( !hasOwnProp( o, k ) ) { + return false; + } + o = o[ k ]; + } + k = keyword[ i ]; + desc = propertyDescriptor( o, k ); + return ( + desc !== null && + ( + // Data descriptor: + desc.writable === false || + + // Accessor descriptor: + ( + typeof desc.get === 'function' && + desc.set === void 0 + ) + ) + ); + } + /** * Loads and evaluates a JavaScript file line-by-line. * From df12bff6013db45f9d1f48fa9d4d3ce657ee75aa Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 22 Mar 2019 01:26:18 -0700 Subject: [PATCH 123/142] Add support for running examples --- .../@stdlib/repl/ctor/lib/create_context.js | 57 +++++++++++++++++-- 1 file changed, 52 insertions(+), 5 deletions(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index c9a5169a437f..2375eace8bbd 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -28,6 +28,7 @@ var Console = require( 'console' ).Console; var logger = require( 'debug' ); var isString = require( '@stdlib/assert/is-string' ).isPrimitive; var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var RE_EOL = require( '@stdlib/regexp/eol' ); var getGlobal = require( '@stdlib/utils/global' ); var objectKeys = require( '@stdlib/utils/keys' ); var propertyDescriptor = require( '@stdlib/utils/property-descriptor' ); @@ -36,6 +37,7 @@ var setConfigurableReadOnly = require( '@stdlib/utils/define-configurable-read-o var alias2pkg = require( '@stdlib/namespace/alias2pkg' ); var alias2related = require( '@stdlib/namespace/alias2related' ); var alias2help = require( '@stdlib/repl/help' ); +var alias2example = require( '@stdlib/repl/code-blocks' ); var indexOf = require( './index_of.js' ); var createRequire = require( './create_require.js' ); var HELP_TEXT = require( './help_text.js' ); @@ -44,6 +46,7 @@ var setAliases = require( './set_aliases.js' ); var setAliasesGlobal = require( './set_aliases_global.js' ); var setCommands = require( './set_commands.js' ); var setCommandsGlobal = require( './set_commands_global.js' ); +var displayPrompt = require( './display_prompt.js' ); // VARIABLES // @@ -124,16 +127,13 @@ function createContext( repl ) { [ 'alias2related', onAlias2Related, false ], [ 'ans', onAns, true ], [ 'clear', onClear, false ], + [ 'example', onExample, false ], [ 'help', onHelp, false ], [ 'isKeyword', isKeyword, false ], [ 'load', onLoad, false ], [ 'quit', onQuit, false ] ]; - // TODO: add `example` command - - // TODO: add `isKeyword` command - // TODO: add `save` command // TODO: add `saveStart` command @@ -246,6 +246,53 @@ function createContext( repl ) { repl.clear(); } + /** + * Runs an example. + * + * @private + * @param {*} alias - variable alias or value + * @returns {void} + */ + function onExample( alias ) { + var aliases; + var out; + var N; + var i; + + aliases = repl._aliases; + N = aliases.length; + + if ( isString( alias ) ) { + out = alias2example( alias ); + } + // If provided an `alias` which is not a string or we failed to resolve an associated example based on the provided string value, we try to resolve a string alias (and subsequently a corresponding example) by searching the list of cached references of global variables/properties... + if ( !out ) { + i = indexOf( N/2, aliases, 2, 1, alias ); + if ( i >= 0 ) { + out = alias2example( aliases[ i-1 ] ); + } + } + // TODO: add support for running examples for REPL-specific namespace + + if ( out ) { + out = out.split( RE_EOL ); + + // Reset the display prompt: + repl._rli.write( '\n' ); + displayPrompt( repl, false ); + + // Forward each line to the REPL readline interface in order to mimic user input... + for ( i = 0; i < out.length; i++ ) { + if ( out[ i ] ) { + repl._rli.write( out[ i ]+'\n' ); + displayPrompt( repl, false ); + } + } + return; + } + repl._ostream.write( 'Error: no example available. Alias: `'+alias+'`.\n' ); + } + /** * Prints help text. * @@ -268,7 +315,7 @@ function createContext( repl ) { if ( isString( alias ) ) { out = alias2help( alias ); } - // If provided an `alias` which is not a string or we failed to resolve a package name based on the provided string value, we try to resolve a string alias (and subsequently a corresponding package name) by searching the list of cached references of global variables/properties... + // If provided an `alias` which is not a string or we failed to resolve a help text based on the provided string value, we try to resolve a string alias (and subsequently a corresponding help text) by searching the list of cached references of global variables/properties... if ( !out ) { i = indexOf( N/2, aliases, 2, 1, alias ); if ( i >= 0 ) { From 5ec19d2b8a855c2a6e4809092a87140127a6ae2a Mon Sep 17 00:00:00 2001 From: kgryte Date: Fri, 22 Mar 2019 01:30:25 -0700 Subject: [PATCH 124/142] Fix logic for evaluating loaded commands --- lib/node_modules/@stdlib/repl/ctor/lib/create_context.js | 4 ++++ lib/node_modules/@stdlib/repl/ctor/lib/main.js | 5 ++++- 2 files changed, 8 insertions(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js index 2375eace8bbd..ac8ba04df3e6 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/create_context.js @@ -396,6 +396,10 @@ function createContext( repl ) { repl._ostream.write( 'Error: '+err.message+'\n' ); return; } + // Reset the display prompt: + repl._rli.write( '\n' ); + displayPrompt( repl, false ); + debug( 'Loading a file...' ); repl.load( fpath ); } diff --git a/lib/node_modules/@stdlib/repl/ctor/lib/main.js b/lib/node_modules/@stdlib/repl/ctor/lib/main.js index 56915cbb96c7..0a0cbcf0f2d9 100644 --- a/lib/node_modules/@stdlib/repl/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/repl/ctor/lib/main.js @@ -236,7 +236,10 @@ setNonEnumerableReadOnly( REPL.prototype, 'load', function load( fpath ) { // Forward each line to the REPL readline interface in order to mimic user input... for ( i = 0; i < file.length; i++ ) { - this._rli.write( file[ i ] ); + if ( file[ i ] ) { + this._rli.write( file[ i ]+'\n' ); + displayPrompt( this, false ); + } } return this; }); From 17be029e082d59e3e86bbe98dcf0a2b5809cbc84 Mon Sep 17 00:00:00 2001 From: rinbo Date: Sat, 23 Mar 2019 14:30:32 +0100 Subject: [PATCH 125/142] Refactor in accordance with pull request comments --- .../@stdlib/math/base/special/cosc/README.md | 44 +++++------ .../cosc/docs/img/equation_cosc_function.svg | 73 +++++++++++++++++++ .../math/base/special/cosc/lib/cosc.js | 2 - 3 files changed, 96 insertions(+), 23 deletions(-) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/docs/img/equation_cosc_function.svg diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/README.md b/lib/node_modules/@stdlib/math/base/special/cosc/README.md index eb45b955346c..adaffcd3d85e 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cosc/README.md @@ -2,7 +2,7 @@ @license Apache-2.0 -Copyright (c) 2018 The Stdlib Authors. +Copyright (c) 2019 The Stdlib Authors. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -24,10 +24,16 @@ limitations under the License.
-The derivative of the normalized [cardinal sine][sinc] function is defined as +The derivative of the normalized [cardinal sine][sinc] is defined as -` { cosc(x) = (cos( PI*x ) - sin( PI*x )/(PI*x)) / x } if x != 0, and 0 if x == 0 ` + +
+ Derivative of the normalized cardinal sine. +
+
+ + @@ -42,7 +48,7 @@ for any real number `x`. ## Usage ```javascript -var cosc = require( '@stdlib/math/base/special/cosc' ); +var cosc = require("@stdlib/math/base/special/cosc"); ``` #### cosc( x ) @@ -50,21 +56,17 @@ var cosc = require( '@stdlib/math/base/special/cosc' ); Computes the derivative of the normalized [cardinal sine][sinc] of a `number`. ```javascript -var v = cosc( 0.5 ); - -// Return ~-1.273 - -var x = cosc( -1.2 ); - -// Return ~0.544 - -var y = cosc( 0.0 ); +var v = cosc(0.5); +// returns ~-1.273 -// Return 0 +v = cosc(-1.2); +// returns ~0.544 -var z = cosc( NaN ); +v = cosc(0.0); +// returns 0 -// Return NaN +v = cosc(NaN); +// returns NaN ```
@@ -78,14 +80,14 @@ var z = cosc( NaN ); ```javascript -var linspace = require( '@stdlib/math/utils/linspace' ); -var cosc = require( '@stdlib/math/base/special/cosc' ); +var linspace = require("@stdlib/math/utils/linspace"); +var cosc = require("@stdlib/math/base/special/cosc"); -var x = linspace( -5.0, 5.0, 100 ); +var x = linspace(-5.0, 5.0, 100); var i; -for ( i = 0; i < x.length; i++ ) { - console.log( cosc( x[ i ] ) ); +for (i = 0; i < x.length; i++) { + console.log(cosc(x[i])); } ``` diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/docs/img/equation_cosc_function.svg b/lib/node_modules/@stdlib/math/base/special/cosc/docs/img/equation_cosc_function.svg new file mode 100644 index 000000000000..8da3aa674beb --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/docs/img/equation_cosc_function.svg @@ -0,0 +1,73 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js index 75d11bc1e980..5ee56d80546c 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js +++ b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js @@ -40,7 +40,6 @@ var PI = require('@stdlib/constants/math/float64-pi'); * \operatorname{cosc}(x) = \frac{\operatorname{cos}(\pi x)}{x} - \frac{\operatorname{sin}(\pi x)}{\pi x^2} * ``` * - * * ## Special Cases * * ```tex @@ -52,7 +51,6 @@ var PI = require('@stdlib/constants/math/float64-pi'); * \end{align*} * ``` * - * * @param {number} x - input value * @returns {number} derivative of normalized sinc(x) * From 19ebafa860f37a6eaf9e32de4c3bb999e52a2fab Mon Sep 17 00:00:00 2001 From: rinbo Date: Sat, 23 Mar 2019 14:47:48 +0100 Subject: [PATCH 126/142] Change 'Return' to 'returns' in several places --- lib/node_modules/@stdlib/math/base/special/cosc/README.md | 2 +- .../@stdlib/math/base/special/cosc/lib/cosc.js | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/README.md b/lib/node_modules/@stdlib/math/base/special/cosc/README.md index adaffcd3d85e..1630b45ea0fe 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cosc/README.md @@ -63,7 +63,7 @@ v = cosc(-1.2); // returns ~0.544 v = cosc(0.0); -// returns 0 +// returns 0.0 v = cosc(NaN); // returns NaN diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js index 5ee56d80546c..aef853bc3d68 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js +++ b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js @@ -56,19 +56,19 @@ var PI = require('@stdlib/constants/math/float64-pi'); * * @example * var v = cosc( 0.5 ) - * // return ~-1.273 + * // returns ~-1.273 * * @example * var v = cosc( -1.2 ) - * // return ~0.544 + * // returns ~0.544 * * @example * var v = cosc( 0.0 ) - * // return 0 + * // returns 0.0 * * @example * var v = cosc( NaN ) - * // return NaN + * // returns NaN */ function cosc(x) { if (isnan(x)) { From de00626ccc2a918bb2c939ea7e82dfd4c836d2c6 Mon Sep 17 00:00:00 2001 From: rinbo Date: Sat, 23 Mar 2019 16:04:53 +0100 Subject: [PATCH 127/142] Remove dublicate comment --- .../@stdlib/math/base/special/cosc/README.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/README.md b/lib/node_modules/@stdlib/math/base/special/cosc/README.md index 1630b45ea0fe..55e93fe90878 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cosc/README.md @@ -26,6 +26,8 @@ limitations under the License. The derivative of the normalized [cardinal sine][sinc] is defined as + +
@@ -35,7 +37,7 @@ The derivative of the normalized [cardinal sine][sinc] is defined as - + for any real number `x`. @@ -48,7 +50,7 @@ for any real number `x`. ## Usage ```javascript -var cosc = require("@stdlib/math/base/special/cosc"); +var cosc = require('@stdlib/math/base/special/cosc'); ``` #### cosc( x ) @@ -80,8 +82,8 @@ v = cosc(NaN); ```javascript -var linspace = require("@stdlib/math/utils/linspace"); -var cosc = require("@stdlib/math/base/special/cosc"); +var linspace = require('@stdlib/math/utils/linspace'); +var cosc = require('@stdlib/math/base/special/cosc'); var x = linspace(-5.0, 5.0, 100); var i; From 1d7216c04daa8eed886f7118291b51c08785a09d Mon Sep 17 00:00:00 2001 From: rinbo Date: Tue, 12 Mar 2019 21:37:54 +0100 Subject: [PATCH 128/142] Add licence header --- .../@stdlib/math/base/special/cosc/README.md | 21 +++++++++++++++++++ 1 file changed, 21 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/README.md diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/README.md b/lib/node_modules/@stdlib/math/base/special/cosc/README.md new file mode 100644 index 000000000000..37cde05d900e --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/README.md @@ -0,0 +1,21 @@ + + +# Computes derivative of the cardinal sine function From b396dc25082f4e98b30b9f46e8648a5f7d67ffe7 Mon Sep 17 00:00:00 2001 From: rinbo Date: Tue, 12 Mar 2019 21:48:01 +0100 Subject: [PATCH 129/142] Add package.json --- .../math/base/special/cosc/package.json | 65 +++++++++++++++++++ 1 file changed, 65 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/package.json diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/package.json b/lib/node_modules/@stdlib/math/base/special/cosc/package.json new file mode 100644 index 000000000000..a135c3511da5 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/math/base/special/cosc", + "version": "0.0.0", + "description": "Compute the derivative of the normalized cardinal sine of a number.", + "license": "Apache-2.0", + "author": { + "name": "Maybe me?", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "sin", + "sinc", + "sine", + "cardinal", + "trig", + "trigonometry", + "normalized", + "cosc" + ] +} From b5ddcdc6ecee2018221c0d02c0ea2d221950593f Mon Sep 17 00:00:00 2001 From: rinbo Date: Wed, 13 Mar 2019 21:21:41 +0100 Subject: [PATCH 130/142] Add cosc.js --- .../math/base/special/cosc/lib/cosc.js | 91 +++++++++++++++++++ .../math/base/special/cosc/package.json | 2 +- 2 files changed, 92 insertions(+), 1 deletion(-) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js new file mode 100644 index 000000000000..75d11bc1e980 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js @@ -0,0 +1,91 @@ +/** + * @license Apache-2.0 + * + * Copyright (c) 2019 The Stdlib Authors. + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +'use strict'; + +// MODULES // + +var sinpi = require('@stdlib/math/base/special/sinpi'); +var cospi = require('@stdlib/math/base/special/cospi'); +var isnan = require('@stdlib/math/base/assert/is-nan'); +var isInfinite = require('@stdlib/math/base/assert/is-infinite'); +var PI = require('@stdlib/constants/math/float64-pi'); + + +// MAIN // + +/** + * Computes the derivative of the normalized cardinal sine of a number. + * + * ## Method + * + * For \\( x \neq 0 \\), the derivative of \operatorname{sinc}(x) is calculated as + * + * ```tex + * \operatorname{cosc}(x) = \frac{\operatorname{cos}(\pi x)}{x} - \frac{\operatorname{sin}(\pi x)}{\pi x^2} + * ``` + * + * + * ## Special Cases + * + * ```tex + * \begin{align*} + * \operatorname{cosc}(0) &= 0 & \\ + * \operatorname{cosc}(\infty) &= 0 & \\ + * \operatorname{cosc}(-\infty) &= 0 & \\ + * \operatorname{cosc}(\mathrm{NaN}) &= \mathrm{NaN} + * \end{align*} + * ``` + * + * + * @param {number} x - input value + * @returns {number} derivative of normalized sinc(x) + * + * @example + * var v = cosc( 0.5 ) + * // return ~-1.273 + * + * @example + * var v = cosc( -1.2 ) + * // return ~0.544 + * + * @example + * var v = cosc( 0.0 ) + * // return 0 + * + * @example + * var v = cosc( NaN ) + * // return NaN + */ +function cosc(x) { + if (isnan(x)) { + return NaN; + } + if (isInfinite(x)) { + return 0.0; + } + if (x === 0.0) { + return 0.0; + } + return ( cospi(x) - ( sinpi(x) / ( PI * x ))) / x; +} + + +// EXPORTS // + +module.exports = cosc; diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/package.json b/lib/node_modules/@stdlib/math/base/special/cosc/package.json index a135c3511da5..8cbfe2f8b032 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/package.json +++ b/lib/node_modules/@stdlib/math/base/special/cosc/package.json @@ -4,7 +4,7 @@ "description": "Compute the derivative of the normalized cardinal sine of a number.", "license": "Apache-2.0", "author": { - "name": "Maybe me?", + "name": "The Stdlib Authors", "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" }, "contributors": [ From 70a9faa31f5cf410a9b8f4067227c623ebd2e679 Mon Sep 17 00:00:00 2001 From: rinbo Date: Wed, 13 Mar 2019 21:25:24 +0100 Subject: [PATCH 131/142] Add index.js for lib dir --- .../math/base/special/cosc/lib/index.js | 49 +++++++++++++++++++ 1 file changed, 49 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/lib/index.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/lib/index.js b/lib/node_modules/@stdlib/math/base/special/cosc/lib/index.js new file mode 100644 index 000000000000..d241c35141b9 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/lib/index.js @@ -0,0 +1,49 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the derivative of the normalized cardinal sine of a number. +* +* @module @stdlib/math/base/special/cosc +* +* @example +* var cosc = require( '@stdlib/math/base/special/cosc' ); +* +* var v = cosc( 0.5 ); +* // returns ~-1.273 +* +* v = cosc( -1.2 ); +* // returns ~-0.544 +* +* v = cosc( 0.0 ); +* // returns 0.0 +* +* v = cosc( NaN ); +* // returns NaN +*/ + +// MODULES // + +var cosc = require( './cosc.js' ); + + +// EXPORTS // + +module.exports = cosc; From 53f1d369196ca746f45b650d0383cbedc024fb8a Mon Sep 17 00:00:00 2001 From: rinbo Date: Wed, 13 Mar 2019 22:19:55 +0100 Subject: [PATCH 132/142] Add Julia test fixtures --- .../cosc/test/fixtures/julia/data.json | 1 + .../test/fixtures/julia/large_negative.json | 1 + .../test/fixtures/julia/large_positive.json | 1 + .../cosc/test/fixtures/julia/runner.jl | 80 +++++++++++++++++++ .../test/fixtures/julia/tiny_negative.json | 1 + .../test/fixtures/julia/tiny_positive.json | 1 + .../math/base/special/cosc/test/tests.js | 0 7 files changed, 85 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/large_negative.json create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/large_positive.json create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json new file mode 100644 index 000000000000..d326f74a2658 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/large_negative.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/large_negative.json new file mode 100644 index 000000000000..f42ea6c60a5f --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/large_negative.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl new file mode 100644 index 000000000000..4b9d7ab2948a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl @@ -0,0 +1,80 @@ +#!/usr/bin/env julia +# +# @license Apache-2.0 +# +# Copyright (c) 2018 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import JSON + +""" + gen( x, name ) + +Generate fixture data and write to file. + +# Arguments + +* `x`: domain +* `name::AbstractString`: output filename + +# Examples + +``` julia +julia> x = range( -708, stop=709, lenght=2001 ); +julia> gen( x, \"data.json\" ); +``` +""" +function gen( x, name ) + y = cosc.( x ); + + # Store data to be written to file as a collection: + data = Dict([ + ("x", x), + ("expected", y) + ]); + + # Based on the script directory, create an output filepath: + filepath = joinpath( dir, name ); + + # Write the data to the output filepath as JSON: + outfile = open( filepath, "w" ); + write( outfile, JSON.json(data) ); + close( outfile ); +end + +# Get the filename: +file = @__FILE__; + +# Extract the directory in which this file resides: +dir = dirname( file ); + +# Generate fixture data for decimal values: +x = LinRange( -100, 100, 4003 ); +gen( x, "data.json" ); + +# Large negative values: +x = LinRange( -709.0895, -100, 1003 ); +gen( x, "large_negative.json" ); + +# Large positive values: +x = LinRange( 100, 710.475, 1003 ); +gen( x, "large_positive.json" ); + +# Tiny negative values: +x = LinRange( -1e-200, -1e-208, 503 ); +gen( x, "tiny_negative.json" ); + +# Tiny positive values: +x = LinRange( 1e-300, 1e-308, 503 ); +gen( x, "tiny_positive.json" ); diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json new file mode 100644 index 000000000000..252dd999d86a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json new file mode 100644 index 000000000000..2bacf65cd5d5 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js b/lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js new file mode 100644 index 000000000000..e69de29bb2d1 From 6477d8426ac79059313fed5bb160612eff195dfd Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 18:10:08 +0100 Subject: [PATCH 133/142] Add fixtures using Julia --- lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js | 0 1 file changed, 0 insertions(+), 0 deletions(-) delete mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js b/lib/node_modules/@stdlib/math/base/special/cosc/test/tests.js deleted file mode 100644 index e69de29bb2d1..000000000000 From 8d379cf4931316d54c7d0c0cd2b1445ecfaae70c Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 22:02:10 +0100 Subject: [PATCH 134/142] Re-run Julia fixture generator and add tests --- .../cosc/test/fixtures/julia/data.json | 2 +- .../cosc/test/fixtures/julia/runner.jl | 4 +- .../math/base/special/cosc/test/test.js | 196 ++++++++++++++++++ 3 files changed, 199 insertions(+), 3 deletions(-) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/test/test.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json index d326f74a2658..4fa25300efd1 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/data.json @@ -1 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl index 4b9d7ab2948a..841a5df1fdff 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl @@ -31,7 +31,7 @@ Generate fixture data and write to file. # Examples ``` julia -julia> x = range( -708, stop=709, lenght=2001 ); +julia> x = range( -708, stop=709, length=2001 ); julia> gen( x, \"data.json\" ); ``` """ @@ -60,7 +60,7 @@ file = @__FILE__; dir = dirname( file ); # Generate fixture data for decimal values: -x = LinRange( -100, 100, 4003 ); +x = LinRange( -100, 100, 1000 ); gen( x, "data.json" ); # Large negative values: diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/test.js b/lib/node_modules/@stdlib/math/base/special/cosc/test/test.js new file mode 100644 index 000000000000..2b7e6ca88c5d --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/test.js @@ -0,0 +1,196 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/math/float64-pinf' ); +var NINF = require( '@stdlib/constants/math/float64-ninf' ); +var EPS = require( '@stdlib/constants/math/float64-eps' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var cosc = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); +var largeNegative = require( './fixtures/julia/large_negative.json' ); +var largePositive = require( './fixtures/julia/large_positive.json' ); +var tinyNegative = require( './fixtures/julia/tiny_negative.json' ); +var tinyPositive = require( './fixtures/julia/tiny_positive.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.equal( typeof cosc, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the derivative of the cardinal sine', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + + x = data.x; + expected = data.expected; + + for ( i = 0; i < x.length; i++ ) { + y = cosc( x[i] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); + } else { + delta = abs( y - expected[i] ); + tol = 2.0 * EPS * abs( expected[i] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. Expected: '+expected[i]+'. Tolerance: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the derivative of the cardinal sine (large negative)', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + + x = largeNegative.x; + expected = largeNegative.expected; + + for ( i = 0; i < x.length; i++ ) { + y = cosc( x[i] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); + } else { + delta = abs( y - expected[i] ); + tol = 2.0 * EPS * abs( expected[i] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. Expected: '+expected[i]+'. Tolerance: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the derivative of the cardinal sine (large positive)', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + + x = largePositive.x; + expected = largePositive.expected; + + for ( i = 0; i < x.length; i++ ) { + y = cosc( x[i] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); + } else { + delta = abs( y - expected[i] ); + tol = 2.0 * EPS * abs( expected[i] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. Expected: '+expected[i]+'. Tolerance: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the derivative of the cardinal sine (tiny negative)', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + + x = tinyNegative.x; + expected = tinyNegative.expected; + + for ( i = 0; i < x.length; i++ ) { + if (expected[i] > 1e+100) // Jump over Julia fixture values that are out of wack + { + continue; + } + y = cosc( x[i] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); + } else { + delta = abs( y - expected[i] ); + tol = EPS * abs( expected[i] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. Expected: '+expected[i]+'. Tolerance: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function computes the derivative of the cardinal sine (tiny positive)', function test( t ) { + var expected; + var delta; + var tol; + var x; + var y; + var i; + + x = tinyPositive.x; + expected = tinyPositive.expected; + + for ( i = 0; i < x.length; i++ ) { + if (expected[i] < -1e+100) // Jump over Julia fixture values that are out of wack + { + continue; + } + y = cosc( x[i] ); + if ( y === expected[ i ] ) { + t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); + } else { + delta = abs( y - expected[i] ); + tol = EPS * abs( expected[i] ); + t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. Value: '+y+'. Expected: '+expected[i]+'. Tolerance: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided a `NaN`', function test( t ) { + var v = cosc( NaN ); + t.equal( isnan( v ), true, 'returns NaN' ); + t.end(); +}); + +tape( 'the function returns `0.0` if provided `0.0`', function test( t ) { + var v = cosc( 0.0 ); + t.equal( v, 0.0, 'returns 0.0' ); + t.end(); +}); + +tape( 'the function returns `0.0` if provided positive or negative infinity', function test( t ) { + var v = cosc( PINF ); + t.equal( v, 0.0, 'returns 0.0' ); + + v = cosc( NINF ); + t.equal( v, 0.0, 'returns 0.0' ); + t.end(); +}); From c3ca92bcf72d37a5751d727f04e1cef9a181b9c7 Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 22:06:11 +0100 Subject: [PATCH 135/142] Add examples --- .../math/base/special/cosc/examples/index.js | 29 +++++++++++++++++++ 1 file changed, 29 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/examples/index.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/examples/index.js b/lib/node_modules/@stdlib/math/base/special/cosc/examples/index.js new file mode 100644 index 000000000000..4dbe8361d1b0 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var linspace = require( '@stdlib/math/utils/linspace' ); +var cosc = require( './../lib' ); + +var x = linspace( -5.0, 5.0, 100 ); +var i; + +for ( i = 0; i < x.length; i++ ) { + console.log( 'cosc( %d ) = %d', x[ i ], cosc( x[ i ] ) ); +} From 9d2dc74899342a95e1d866d7075df4d52143c4ec Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 22:13:29 +0100 Subject: [PATCH 136/142] Add benchmark --- .../base/special/cosc/benchmark/benchmark.js | 51 +++++++++++++++++++ 1 file changed, 51 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/benchmark/benchmark.js diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/special/cosc/benchmark/benchmark.js new file mode 100644 index 000000000000..4f78c522951a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/benchmark/benchmark.js @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2018 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var cosc = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var x; + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x = ( randu() * 2.0 ) - 2.0; + y = cosc( x ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); From 9effbe6cc6a1766dab1ede6398b06bd8855cef80 Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 22:21:05 +0100 Subject: [PATCH 137/142] Add typescript examples and test --- .../base/special/cosc/docs/types/index.d.ts | 48 +++++++++++++++++++ .../math/base/special/cosc/docs/types/test.ts | 44 +++++++++++++++++ 2 files changed, 92 insertions(+) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/docs/types/index.d.ts create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/docs/types/test.ts diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/index.d.ts new file mode 100644 index 000000000000..3e42dec1e01b --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/index.d.ts @@ -0,0 +1,48 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 2.0 + +/** +* Computes the derivative of the normalized cardinal sine of a number. +* +* @param x - input value +* @returns derivative of cardinal sine +* +* @example +* var v = cosc( 0.5 ); +* // returns ~-1.273 +* +* @example +* var v = cosc( -1.2 ); +* // returns ~0.544 +* +* @example +* var v = cosc( 0.0 ); +* // returns 0.0 +* +* @example +* var v = cosc( NaN ); +* // returns NaN +*/ +declare function cosc( x: number ): number; + + +// EXPORTS // + +export = cosc; diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/test.ts b/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/test.ts new file mode 100644 index 000000000000..977afeb44a82 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/docs/types/test.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2019 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import cosc = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + cosc( 8 ); // $ExpectType number +} + +// The function does not compile if provided a value other than a number... +{ + cosc( true ); // $ExpectError + cosc( false ); // $ExpectError + cosc( null ); // $ExpectError + cosc( undefined ); // $ExpectError + cosc( '5' ); // $ExpectError + cosc( [] ); // $ExpectError + cosc( {} ); // $ExpectError + cosc( ( x: number ): number => x ); // $ExpectError +} + +// The function does not compile if provided insufficient arguments... +{ + cosc(); // $ExpectError +} From aee020e825c682a760c9e57ca2d6b6fda66eb928 Mon Sep 17 00:00:00 2001 From: rinbo Date: Thu, 14 Mar 2019 23:06:42 +0100 Subject: [PATCH 138/142] Update readme --- .../@stdlib/math/base/special/cosc/README.md | 83 ++++++++++++++++++- 1 file changed, 82 insertions(+), 1 deletion(-) diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/README.md b/lib/node_modules/@stdlib/math/base/special/cosc/README.md index 37cde05d900e..eb45b955346c 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cosc/README.md @@ -18,4 +18,85 @@ limitations under the License. --> -# Computes derivative of the cardinal sine function +# cosc + +> Compute the derivative of the [cardinal sine][sinc] of a number. + +
+ +The derivative of the normalized [cardinal sine][sinc] function is defined as + +` { cosc(x) = (cos( PI*x ) - sin( PI*x )/(PI*x)) / x } if x != 0, and 0 if x == 0 ` + + + + +for any real number `x`. + +
+ + + +
+ +## Usage + +```javascript +var cosc = require( '@stdlib/math/base/special/cosc' ); +``` + +#### cosc( x ) + +Computes the derivative of the normalized [cardinal sine][sinc] of a `number`. + +```javascript +var v = cosc( 0.5 ); + +// Return ~-1.273 + +var x = cosc( -1.2 ); + +// Return ~0.544 + +var y = cosc( 0.0 ); + +// Return 0 + +var z = cosc( NaN ); + +// Return NaN +``` + +
+ + + +
+ +## Examples + + + +```javascript +var linspace = require( '@stdlib/math/utils/linspace' ); +var cosc = require( '@stdlib/math/base/special/cosc' ); + +var x = linspace( -5.0, 5.0, 100 ); +var i; + +for ( i = 0; i < x.length; i++ ) { + console.log( cosc( x[ i ] ) ); +} +``` + +
+ + + +
+ +[sinc]: https://en.wikipedia.org/wiki/Sinc_function + +
+ + From 3381152e622308292aefe8083277df9433de4516 Mon Sep 17 00:00:00 2001 From: rinbo Date: Sat, 23 Mar 2019 14:30:32 +0100 Subject: [PATCH 139/142] Refactor in accordance with pull request comments --- .../@stdlib/math/base/special/cosc/README.md | 44 +++++------ .../cosc/docs/img/equation_cosc_function.svg | 73 +++++++++++++++++++ .../math/base/special/cosc/lib/cosc.js | 2 - 3 files changed, 96 insertions(+), 23 deletions(-) create mode 100644 lib/node_modules/@stdlib/math/base/special/cosc/docs/img/equation_cosc_function.svg diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/README.md b/lib/node_modules/@stdlib/math/base/special/cosc/README.md index eb45b955346c..adaffcd3d85e 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cosc/README.md @@ -2,7 +2,7 @@ @license Apache-2.0 -Copyright (c) 2018 The Stdlib Authors. +Copyright (c) 2019 The Stdlib Authors. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. @@ -24,10 +24,16 @@ limitations under the License.
-The derivative of the normalized [cardinal sine][sinc] function is defined as +The derivative of the normalized [cardinal sine][sinc] is defined as -` { cosc(x) = (cos( PI*x ) - sin( PI*x )/(PI*x)) / x } if x != 0, and 0 if x == 0 ` + +
+ Derivative of the normalized cardinal sine. +
+
+ + @@ -42,7 +48,7 @@ for any real number `x`. ## Usage ```javascript -var cosc = require( '@stdlib/math/base/special/cosc' ); +var cosc = require("@stdlib/math/base/special/cosc"); ``` #### cosc( x ) @@ -50,21 +56,17 @@ var cosc = require( '@stdlib/math/base/special/cosc' ); Computes the derivative of the normalized [cardinal sine][sinc] of a `number`. ```javascript -var v = cosc( 0.5 ); - -// Return ~-1.273 - -var x = cosc( -1.2 ); - -// Return ~0.544 - -var y = cosc( 0.0 ); +var v = cosc(0.5); +// returns ~-1.273 -// Return 0 +v = cosc(-1.2); +// returns ~0.544 -var z = cosc( NaN ); +v = cosc(0.0); +// returns 0 -// Return NaN +v = cosc(NaN); +// returns NaN ```
@@ -78,14 +80,14 @@ var z = cosc( NaN ); ```javascript -var linspace = require( '@stdlib/math/utils/linspace' ); -var cosc = require( '@stdlib/math/base/special/cosc' ); +var linspace = require("@stdlib/math/utils/linspace"); +var cosc = require("@stdlib/math/base/special/cosc"); -var x = linspace( -5.0, 5.0, 100 ); +var x = linspace(-5.0, 5.0, 100); var i; -for ( i = 0; i < x.length; i++ ) { - console.log( cosc( x[ i ] ) ); +for (i = 0; i < x.length; i++) { + console.log(cosc(x[i])); } ``` diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/docs/img/equation_cosc_function.svg b/lib/node_modules/@stdlib/math/base/special/cosc/docs/img/equation_cosc_function.svg new file mode 100644 index 000000000000..8da3aa674beb --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/cosc/docs/img/equation_cosc_function.svg @@ -0,0 +1,73 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js index 75d11bc1e980..5ee56d80546c 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js +++ b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js @@ -40,7 +40,6 @@ var PI = require('@stdlib/constants/math/float64-pi'); * \operatorname{cosc}(x) = \frac{\operatorname{cos}(\pi x)}{x} - \frac{\operatorname{sin}(\pi x)}{\pi x^2} * ``` * - * * ## Special Cases * * ```tex @@ -52,7 +51,6 @@ var PI = require('@stdlib/constants/math/float64-pi'); * \end{align*} * ``` * - * * @param {number} x - input value * @returns {number} derivative of normalized sinc(x) * From c8b7445edc41449c52830e600ff7bf606de01a22 Mon Sep 17 00:00:00 2001 From: rinbo Date: Sat, 23 Mar 2019 14:47:48 +0100 Subject: [PATCH 140/142] Change 'Return' to 'returns' in several places --- lib/node_modules/@stdlib/math/base/special/cosc/README.md | 2 +- .../@stdlib/math/base/special/cosc/lib/cosc.js | 8 ++++---- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/README.md b/lib/node_modules/@stdlib/math/base/special/cosc/README.md index adaffcd3d85e..1630b45ea0fe 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cosc/README.md @@ -63,7 +63,7 @@ v = cosc(-1.2); // returns ~0.544 v = cosc(0.0); -// returns 0 +// returns 0.0 v = cosc(NaN); // returns NaN diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js index 5ee56d80546c..aef853bc3d68 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js +++ b/lib/node_modules/@stdlib/math/base/special/cosc/lib/cosc.js @@ -56,19 +56,19 @@ var PI = require('@stdlib/constants/math/float64-pi'); * * @example * var v = cosc( 0.5 ) - * // return ~-1.273 + * // returns ~-1.273 * * @example * var v = cosc( -1.2 ) - * // return ~0.544 + * // returns ~0.544 * * @example * var v = cosc( 0.0 ) - * // return 0 + * // returns 0.0 * * @example * var v = cosc( NaN ) - * // return NaN + * // returns NaN */ function cosc(x) { if (isnan(x)) { From cf65b8fcbe4b222ad60251b69cbee39249562bb2 Mon Sep 17 00:00:00 2001 From: rinbo Date: Sat, 23 Mar 2019 16:04:53 +0100 Subject: [PATCH 141/142] Remove dublicate comment --- .../@stdlib/math/base/special/cosc/README.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/README.md b/lib/node_modules/@stdlib/math/base/special/cosc/README.md index 1630b45ea0fe..55e93fe90878 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cosc/README.md @@ -26,6 +26,8 @@ limitations under the License. The derivative of the normalized [cardinal sine][sinc] is defined as + +
@@ -35,7 +37,7 @@ The derivative of the normalized [cardinal sine][sinc] is defined as - + for any real number `x`. @@ -48,7 +50,7 @@ for any real number `x`. ## Usage ```javascript -var cosc = require("@stdlib/math/base/special/cosc"); +var cosc = require('@stdlib/math/base/special/cosc'); ``` #### cosc( x ) @@ -80,8 +82,8 @@ v = cosc(NaN); ```javascript -var linspace = require("@stdlib/math/utils/linspace"); -var cosc = require("@stdlib/math/base/special/cosc"); +var linspace = require('@stdlib/math/utils/linspace'); +var cosc = require('@stdlib/math/base/special/cosc'); var x = linspace(-5.0, 5.0, 100); var i; From c0fa3e030536d9463855d66a54bf675c3cffd9cd Mon Sep 17 00:00:00 2001 From: rinbo Date: Wed, 27 Mar 2019 21:42:14 +0100 Subject: [PATCH 142/142] Update julia fixtures with values for x that don't run into julia precision error --- .../math/base/special/cosc/test/fixtures/julia/runner.jl | 4 ++-- .../special/cosc/test/fixtures/julia/tiny_negative.json | 2 +- .../special/cosc/test/fixtures/julia/tiny_positive.json | 2 +- .../@stdlib/math/base/special/cosc/test/test.js | 8 -------- 4 files changed, 4 insertions(+), 12 deletions(-) diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl index 841a5df1fdff..e9c90ea9d4a3 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/runner.jl @@ -72,9 +72,9 @@ x = LinRange( 100, 710.475, 1003 ); gen( x, "large_positive.json" ); # Tiny negative values: -x = LinRange( -1e-200, -1e-208, 503 ); +x = rand(Float64, 10)*-10e-200; gen( x, "tiny_negative.json" ); # Tiny positive values: -x = LinRange( 1e-300, 1e-308, 503 ); +x = rand(Float64, 10)*10e-200; gen( x, "tiny_positive.json" ); diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json index 252dd999d86a..85ca61c2cb45 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_negative.json @@ -1 +1 @@ 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\ No newline at end of file +{"expected":[-0.0,-0.0,-0.0,-0.0,-0.0,-0.0,-0.0,-0.0,-0.0,-0.0],"x":[-9.195873370788277e-200,-9.006868205451577e-200,-2.0302704881108302e-200,-4.697124158384864e-200,-4.52038739950706e-200,-2.1491068965578065e-201,-3.0590073997056775e-200,-3.835325822891831e-200,-7.378509868591106e-200,-7.233945087169975e-200]} \ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json index 2bacf65cd5d5..ca26f1494b1b 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/fixtures/julia/tiny_positive.json @@ -1 +1 @@ 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\ No newline at end of file +{"expected":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0],"x":[7e-200,3.4561630239884523e-200,9.238493513228763e-201,7.329068948020792e-200,3.987926967580968e-201,3.412898694594113e-201,4e-200,4.178006140387547e-201,5.955777198110583e-200,5.736111313659942e-201]} diff --git a/lib/node_modules/@stdlib/math/base/special/cosc/test/test.js b/lib/node_modules/@stdlib/math/base/special/cosc/test/test.js index 2b7e6ca88c5d..f89bea6a9880 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosc/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/cosc/test/test.js @@ -130,10 +130,6 @@ tape( 'the function computes the derivative of the cardinal sine (tiny negative) expected = tinyNegative.expected; for ( i = 0; i < x.length; i++ ) { - if (expected[i] > 1e+100) // Jump over Julia fixture values that are out of wack - { - continue; - } y = cosc( x[i] ); if ( y === expected[ i ] ) { t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); @@ -158,10 +154,6 @@ tape( 'the function computes the derivative of the cardinal sine (tiny positive) expected = tinyPositive.expected; for ( i = 0; i < x.length; i++ ) { - if (expected[i] < -1e+100) // Jump over Julia fixture values that are out of wack - { - continue; - } y = cosc( x[i] ); if ( y === expected[ i ] ) { t.equal( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] );